Hasil untuk "Special aspects of education"

Fatima Zahra Ramdani, Mohamed Merzouki, Laila Lahlou et al.

In Morocco, the legislation of cannabis marks a significant political shift that warrants thorough analysis. This study aims to identify the attitudes of young Moroccans towards the new cannabis regulations and their perceptions of its future consequences. A questionnaire was administered to a sample of 4040 participants, including high school and university students in southern Morocco. The results revealed that females were significantly more likely to be opposed to medical cannabis use (MCU) compared to males and believed more strongly that the law would discourage users from abstaining. Additionally, females were significantly more likely to be against the recreational use of cannabis (RCU). In contrast, tobacco smokers, cannabis users, and participants with depression were more favourable towards MCU legislation. Further studies on young people’s perceptions of cannabis and its effects remain crucial for public health and prevention policy-makers.

Zoe S Oftring, Kim Deutsch, Daniel Tolks et al.

Abstract BackgroundArtificial intelligence (AI) systems are becoming increasingly relevant in everyday clinical practice, with Food and Drug Administration–approved AI solutions now available in many specialties. This development has far-reaching implications for doctors and the future medical profession, highlighting the need for both practicing physicians and medical students to acquire the knowledge, skills, and attitudes necessary to effectively use and evaluate these technologies. Currently, however, there is limited experience with AI-focused curricular training and continuing education. ObjectiveThis paper first introduces a novel blended learning curriculum including one module on AI for medical students in Germany. Second, this paper presents findings from a qualitative postcourse evaluation of students’ knowledge and attitudes toward AI and their overall perception of the course. MethodsClinical-year medical students can attend a 5-day elective course called “Medicine in the Digital Age,” which includes one dedicated AI module alongside 4 others on digital doctor-patient communication; digital health applications and smart devices; telemedicine; and virtual/augmented reality and robotics. After course completion, participants were interviewed in semistructured small group interviews. The interview guide was developed deductively from existing evidence and research questions compiled by our group. A subset of interview questions focused on students’ knowledge, skills, and attitudes regarding medical AI, and their overall course assessment. Responses were analyzed using Mayring’s qualitative content analysis. This paper reports on the subset of students’ statements about their perception and attitudes toward AI and the elective’s general evaluation. ResultsWe conducted a total of 18 group interviews, in which all 35 (100%) participants (female=11, male=24) from 3 consecutive course runs participated. This produced a total of 214 statements on AI, which were assigned to the 3 main categories “Areas of Application,” “Future Work,” and “Critical Reflection.” The findings indicate that students have a nuanced and differentiated understanding of AI. Additionally, 610 statements concerned the elective’s overall assessment, demonstrating great learning benefits and high levels of acceptance of the teaching concept. All 35 students would recommend the elective to peers. ConclusionsThe evaluation demonstrated that the AI module effectively generates competences regarding AI technology, fosters a critical perspective, and prepares medical students to engage with the technology in a differentiated manner. The curriculum is feasible, beneficial, and highly accepted among students, suggesting it could serve as a teaching model for other medical institutions. Given the growing number and impact of medical AI applications, there is a pressing need for more AI-focused curricula and further research on their educational impact.

Nora Alshareef, Sabir Giga, Ian Fletcher

Medical school can be a difficult and emotionally turbulent experience for students. Test anxiety is very common among medical students and may impact their academic performance. However, there is a lack of qualitative studies on test anxiety and emotion regulation in relation to the academic performance of medical students. This study aims to examine the relationship between test anxiety and academic performance among medical students, exploring the role of emotion regulation and coping strategies in managing test anxiety during examinations. The study involved 22 medical students from one Saudi medical school who participated in semi-structured interviews. The interviews were recorded and transcribed verbatim. A thematic analysis was conducted on the transcribed data, resulting in the identification of four key themes. The emerging themes are test anxiety, academic performance, emotion regulation, and other coping strategies. Students’ anxiety can vary from a source of motivation to a severe obstacle. It impacts their theoretical understanding, practical abilities, and the evaluation criteria used to assess academic achievement. However, some students use both adaptive and maladaptive emotion regulation strategies. Promoting emotion regulation and various coping mechanisms to address test anxiety in medical students is essential to enhance their academic performance and prepare them for future healthcare professions.

María Luz Prados, Lucas Brun, María Lorena Brance et al.

Este trabajo tuvo como objetivo principal analizar la problemática del abandono en el primer año de la carrera de Medicina de la Facultad de Ciencias Médicas (FCM) de la Universidad Nacional de Rosario (UNR, Argentina) desde la mirada de los/as estudiantes. A nivel metodológico se posiciona desde la perspectiva del estudio de casos, adoptando a la FCM-UNR como caso instrumental e intrínseco, para lo que se implementaron estrategias metodológicas de recolección de datos mixtas cuanti-cualitativas. Se indagaron las percepciones de estudiantes de la cohorte 2020 en dos momentos del año y entre las principales dimensiones de análisis se hallaron los obstáculos en el ingreso a la vida universitaria y las causales de abandono. A partir de los resultados nos fue posible reflexionar en torno a la relación entre las políticas de ingreso institucional y la relativa democratización de la educación superior y destacar algunas particularidades de la institución bajo estudio.

Abdoul Diallo, William Gilbert, David Litalien et al.

The COVID-19 pandemic has led to an increase in cheating, accelerating a trend that has been ongoing in universities for decades. Although some teaching practices, such as supporting students’ autonomy, are associated with reduced cheating, it is unclear how these associations have evolved during the pandemic. Our study, grounded in self-determination theory, examines how teaching practices perceived as supportive and/or thwarting to basic psychological needs (BPN) are associated with students’ cheating before and during the COVID-19 pandemic. Structural equation modeling results on samples of 1,783 (pre-pandemic) and 1,053 (during the pandemic) students revealed that teaching practices that affect BPN are associated with cheating. This association is stronger before the pandemic than it is during the pandemic, suggesting a shift in teacher-student dynamics. Overall, low levels of BPN support and high levels of BPN thwarting predict student cheating. Relatedness thwarting specifically emerges as a positive predictor of cheating at both time points. These results highlight that predictors of cheating are not necessarily involved with rising cases, as was the case during the COVID-19 pandemic or, perhaps, over the last few decades.

Ewelina Gajewska, Michal Wawer, Katarzyna Budzynska et al.

Computer-aided teacher training is a state-of-the-art method designed to enhance teachers' professional skills effectively while minimising concerns related to costs, time constraints, and geographical limitations. We investigate the potential of large language models (LLMs) in teacher education, using a case of teaching hate incidents management in schools. To this end, we create a multi-agent LLM-based system that mimics realistic situations of hate, using a combination of retrieval-augmented prompting and persona modelling. It is designed to identify and analyse hate speech patterns, predict potential escalation, and propose effective intervention strategies. By integrating persona modelling with agentic LLMs, we create contextually diverse simulations of hate incidents, mimicking real-life situations. The system allows teachers to analyse and understand the dynamics of hate incidents in a safe and controlled environment, providing valuable insights and practical knowledge to manage such situations confidently in real life. Our pilot evaluation demonstrates teachers' enhanced understanding of the nature of annotator disagreements and the role of context in hate speech interpretation, leading to the development of more informed and effective strategies for addressing hate in classroom settings.

Meagan Sundstrom, Justin Gambrell, Adrienne L. Traxler et al.

An increasing number of studies in physics education research use social network analysis to quantify interactions among students. These studies typically gather data through online surveys using one of two different survey formats: recognition, where students select peers' names from a provided course roster, and recall, where students type their peers' names from memory as an open response. These survey formats, however, may be subject to two possible systematic errors. First, students may report more peers' names on a recognition survey than a recall survey because the course roster facilitates their memory of their interactions, whereas they may only remember a subset of their interactions on the recall format. Second, recognition surveys may be subject to name order effects, where students are more likely to select peers' names that appear early on in the roster than those that appear later on (e.g., due to survey fatigue). Here we report the results of two methodological studies of these possible errors in the context of introductory physics courses: one directly comparing 65 student responses to recognition and recall versions of the same network survey prompt, and the other measuring name order effects on 54 recognition surveys from 27 different courses. We find that students may report more peer interactions on a recognition survey than a recall survey and that most recognition surveys are not subject to significant name order effects. These results help to inform survey design for future network studies in physics education research.

Sherri Harms

Providing computer science (CS) offerings in the K-12 education system is often limited by the lack of experienced teachers, especially in small or rural underserved school districts. By helping teachers in underserved areas develop CS curriculum and helping them become certified to teach CS courses, more young people in underserved areas are aware of IT-career opportunities, and prepared for CS education at the university level, which ultimately helps tackle the IT workforce deficit in the United States. This paper discusses a successful implementation of a Google CS4HS grant to a rural underserved area, as well as lessons learned through the implementation of the program. Key elements in the implementation included a face-to-face hands-on workshop, followed by a seven week graduate-level online summer course for the teachers to learn and develop curriculum that covers the CS concepts they will be teaching. The teachers were supported with an online community of practice for the year as they implemented the curriculum.

Karen D. Wang, Zhangyang Wu, L'Nard Tufts et al.

Developing problem-solving competency is central to Science, Technology, Engineering, and Mathematics (STEM) education, yet translating this priority into effective approaches to problem-solving instruction and assessment remain a significant challenge. The recent proliferation of generative artificial intelligence (genAI) tools like ChatGPT in higher education introduces new considerations about how these tools can help or hinder students' development of STEM problem-solving competency. Our research examines these considerations by studying how and why college students use genAI tools in their STEM coursework, focusing on their problem-solving support. We surveyed 40 STEM college students from diverse U.S. institutions and 28 STEM faculty to understand instructor perspectives on effective genAI tool use and guidance in STEM courses. Our findings reveal high adoption rates and diverse applications of genAI tools among STEM students. The most common use cases include finding explanations, exploring related topics, summarizing readings, and helping with problem-set questions. The primary motivation for using genAI tools was to save time. Moreover, over half of student participants reported simply inputting problems for AI to generate solutions, potentially bypassing their own problem-solving processes. These findings indicate that despite high adoption rates, students' current approaches to utilizing genAI tools often fall short in enhancing their own STEM problem-solving competencies. The study also explored students' and STEM instructors' perceptions of the benefits and risks associated with using genAI tools in STEM education. Our findings provide insights into how to guide students on appropriate genAI use in STEM courses and how to design genAI-based tools to foster students' problem-solving competency.

Tor Ole B. Odden, Halvor Tyseng, Jonas Timmann Mjaaland et al.

We propose a technique for performing deductive qualitative data analysis at scale on text-based data. Using a natural language processing technique known as text embeddings, we create vector-based representations of texts in a high-dimensional meaning space within which it is possible to quantify differences as vector distances. To apply the technique, we build off prior work that used topic modeling via Latent Dirichlet Allocation to thematically analyze 18 years of the Physics Education Research Conference proceedings literature. We first extend this analysis through 2023. Next, we create embeddings of all texts and, using representative articles from the 10 topics found by the LDA analysis, define centroids in the meaning space. We calculate the distances between every article and centroid and use the inverted, scaled distances between these centroids and articles to create an alternate topic model. We benchmark this model against the LDA model results and show that this embeddings model recovers most of the trends from that analysis. Finally, to illustrate the versatility of the method we define 8 new topic centroids derived from a review of the physics education research literature by Docktor and Mestre (2014) and re-analyze the literature using these researcher-defined topics. Based on these analyses, we critically discuss the features, uses, and limitations of this method and argue that it holds promise for flexible deductive qualitative analysis of a wide variety of text-based data that avoids many of the drawbacks inherent to prior NLP methods.

Neuza Bertoni Pinto

Com o objetivo de compreender diferenças de itinerários investigativos de pesquisas vinculadas ao campo da Educação Matemática, este artigo analisa um estudo do campo da Didática, e outro, da História da educação matemática.  Com o foco no processo de ensino e aprendizagem da matemática, Pinto (2000) analisa o erro a partir de conceitos e procedimentos da Didática. Defende a ideia de que, além de um observável para o aluno o erro seja, também, um observável para o professor. Investigando, em diferentes vagas pedagógicas, transformações do erro que repercutiram na matemática do ensino, Valente (2022) analisa representações do erro mostrando que, em tempos da consolidação da pedagogia científica de base estatística, a responsabilidade do erro, anteriormente atribuída ao aluno, é direcionada ao trabalho do professor. Apesar de itinerários diferentes, as duas abordagens apresentam convergências em relação aos responsáveis pelo erro. Entretanto, ao abordar transformações transcorridas em um tempo de longa duração, o itinerário histórico distancia-se do didático ao sinalizar para o novo sentido dado ao erro pela matemática do ensino. Destacando o impacto da tecnologia na cultura escolar, em tempos mais recentes, o estudo histórico aponta para o deslocamento da exatidão do cálculo para a calculadora e a busca do erro no processo de aproximação ao resultado apresentado pelo aluno.

Teuku Fadhli, Dominikus David Biondi Situmorang, Nurbaity Nurbaity

This study aims to look at the basic assumptions of individuals towards self-resilience after trauma due to the COVID-19 Pandemic, this study uses an e-research research method by distributing  CBI  questionnaires  from  google  form  through  social  media  in  order  to  obtain relevant information from various random respondents. While the data analysis technique was carried out by frequency distribution analysis to get the average percentage value of the research results. After analysing the percentage, it was found that the basic assumptions of individuals towards self-resilience after the COVID-19 pandemic with an average percentage of 7.73% VU, 7.720 NS, 18.33 NQR, 34.22% AP, and 32.43% VS. So the results of this study indicate that positive post-traumatic changes towards individual resilience due to the COVID-19 Pandemic occur very realistic changes, where individual resilience can be categorised as very transformational, where individual changes and mental development are much better than the pre-trauma situation before the COVID-19 Pandemic occurred.

Purwoko Haryadi Santoso, Edi Istiyono, Haryanto et al.

Light phenomena conceptual assessment (LPCA) is a conceptual survey of light phenomena that has been recently established by the physics education research (PER) scholars. Studying the LPCA psychometric properties is always imperative to inform its measurement validity to potential LPCA users or beyond general educational researchers. Classical Test Theory (CTT) and Item Response Theory (IRT) are two popular statistical frameworks that can be utilized to explore the LPCA measurement validity. To our knowledge, no PER studies have been attempted to make a head-to-head comparison of those methods while validating the LPCA. This study was the first to delineate the LPCA measurement by statistically comparing the CTT and IRT based analysis. The LPCA dataset was drawn from physics students of eight secondary schools presented by Ndihokubwayo et al (2020). Our results accomplished the harmony between the CTT and IRT arguments to estimate the LPCA item performance and students' ability probed by the LPCA. They supported that the LPCA may be used as inventory for evaluating conceptual understanding of light phenomena from low to high students' ability range even some flagged LPCA items were exist based on CTT and IRT arguments. Special considerations for further refinement related to the discriminating power for some problematic LPCA items are discussed.

Eliot Jane Walton

An analysis of barriers to women's participation in physics education is presented. It is expected that in undergraduate physics the most common situation for a women is that she is cisgender and one of a numerical minority in the classroom. The effects of other intersectional identities are not considered. The analysis is based on evidence from the author's lived experience as a transgender woman who transitioned as an undergraduate and on evidence from the literature on the effects of gender differences in academic disciplines. It is expected that the teaching philosophy and practice in physics classrooms favours men over women and these gender dynamics are partially responsible for the under-representation of women in physics. These expectations require further research to be substantiated.

Enzo Bonacci

In the years 2015-2018, the Italian Ministry of Education, University and Research and the Italian Ministry of Defense proposed the joint initiative "Space for Your Future. The ISS: Innovatio, Scientia, Sapientia" in partnership with the Italian Space Agency. It was a competition addressed to secondary school students and aimed at developing innovative experiments to be conducted on the International Space Station, whose acronym (ISS) is the same of the Latin words "Innovatio, Scientia, Sapientia". Regardless of the odds of winning, "Space for Your Future" became a successful STEM educational project implemented in numerous schools. We illustrate how that Astronomy contest fostered a valid constructivist learning, a fruitful participatory science, and vast scientific research. We discuss, in particular, the activities of two teams of pupils from the Scientific High School "Giovanni Battista Grassi" in Latina (seat of the Planetarium "Livio Gratton") who participated within the thematic area No. 3 "Test the Sciences in Space". They all worked on chemical tests, suitable for the ISS microgravity, under the tutoring of Francesco Giuliano (Province Manager of the IYA 2009 and the IYC 2011 in Latina). The key reference is a talk given in the 104th annual congress of the Italian Physical Society at the University of Calabria (September 17-21, 2018) together with an invited lecture held in the 13th European Researchers' Night by Frascati Scienza (September 28, 2018).

Alessandro Ercoli, Vittorio Lubicz

We present an educational proposal which aims to illustrate the elegant, refined and coherent physics contained in Thermodynamics, through a path which assigns to the microscopic description of the physical systems a constantly privileged role. This approach allows to reach a simple and, at the same time, deep understanding of the laws of Thermodynamics, while still emphasizing their great generality, which permits their application to all macroscopic systems, from simple gases to black holes, arriving to characterize the evolution of the entire Universe.

Catherine Riegle-Crumb, Karisma Morton, Chelsea Moore et al.

Owing to their potential impact on students' cognitive and non-cognitive outcomes, the negative attitudes towards science held by many elementary teachers are a critical issue that needs to be addressed. This study focuses on the science education of pre-service elementary teachers with the goal of improving their attitudes before they begin their professional lives as classroom teachers. Specifically, this study builds on a small body of research to examine whether exposure to inquiry-based science content courses that actively involve students in the collaborative process of learning and discovery can promote a positive change in attitudes toward science across several different dimensions. To examine this issue, surveys and administrative data were collected from over 200 students enrolled in the Hands-on-Science (HoS) program for pre-service teachers at the University of Texas at Austin, as well as more than 200 students in a comparison group enrolled in traditional lecture-style classes. Quantitative analyses reveal that after participating in HoS courses, pre-service teachers significantly increased their scores on scales measuring confidence, enjoyment, anxiety, and perceptions of relevance, while those in the comparison group experienced a decline in favorable attitudes to science. These patterns offer empirical support for the attitudinal benefits of inquiry-based instruction and have implications for the future learning opportunities available to students at all education levels.

Idris Skloul Ibrahim, Benjamin Kenwright

The Internet of Things (IoT) has many applications in our daily lives. One aspect in particular is how the IoT is making a substantial impact on education and learning; as we move into the 'Smart Educational' era. This article explores how the IoT continues to transform the education landscape, from classrooms and assessments to culture and attitudes. Smart Education is a pivotal tool in the fight to meet the educational challenges of tomorrow. The IoT tools are getting used more and more often in the area of education, aiming to increase student engagement, satisfaction and quality of learning. IoT will reshape student culture and habits beyond belief. As Smart Education is more than just using technologies, it involves a whole range of factors, from the educational management through to the pedagogical techniques and effectiveness. Educators in the 21st century now have access to gamification, smart devices, data management, and immersive technologies. Enabling academics to gather a variety of information from students. Ranging from monitoring student engagement to adapting the learning strategies for improved learning effectiveness. Through Smart Education, educators will be able to better monitor the needs of individual students and adjust their learning load correspondingly (i.e., optimal learning environment/workload to support and prevent students failing). One of the biggest challenges for educators is how new technologies will address growing problems (engagement and achievement). The scale and pace of change (technological IoT era) is unprecedented. Typically, jobs students are trained for today will not be here tomorrow. Education is not just about knowledge acquisition, but also the digital skills, adaptability and creativity (essential, if students are to thrive in the new world).

Rafael BARBOSA, Ricardo SOUZA

Software is usually considered enabler for innovation in education. Thus, it is necessary to investigate: What leads to innovation in education and which, therefore, should be considered in the development of educational software? How to support decision-making for choosing software to be used in teaching and learning? How to evaluate software that enables, transforms, or supports innovation in education? In order to answer these questions, a research work was conducted that resulted in an approach called DEISE, which is concerned with drivers that lead to innovation in education and indicators that measure the fostering of software to skills need to students for 21st century learning. Through a web system developed for technological support to the DEISE approach, a set of educational software was evaluated by educators and the results show the index of innovation in education for each evaluated software and a comparison between educational software of similar purpose.