Hasil untuk "History of education"

E. Glasersfeld

Juebei Chen, A. Kolmos, Xiangyun Du

ABSTRACT During the last 40 years, problem- and project-based learning (PBL) has been widely adopted in engineering education because of its expected effectiveness in developing students’ professional knowledge and transferable skills. With a growing number of PBL researches and practices in engineering education, systematic or meta-analysis reviews were conducted regarding the definitions, history and development of PBL, and benefits for student learning outcomes. However, challenges in PBL implementation was little addressed in the current review works, and even less attention has been paid on how these challenges in implementation are related to the diverse PBL practices. This paper reviewed 108 research articles to explore the levels at which the currently reported PBL practice is being implemented, and what challenges in PBL practices are being addressed. This research illustrates the variety of PBL implementation at the course level, cross-course level, curriculum level, and project level. Across these four levels, similar challenges are reported at the individual level for teachers and students, as well as at the institutional level and the culture level. Recommendations on future research directions for engineering educational researchers and suggestions for engineering faculty and staff are proposed to optimise PBL curriculum design and inform future PBL implementation.

Christoph Kulgemeyer, Anna Weißbach, Kasim Costan et al.

Evidence-based education has become a central concept in science education, with meta-analyses often regarded as the gold standard for informing practice. This emphasis raises critical questions concerning the applicability, generalizability and transferability of research findings into classroom practice. It remains unclear both what kind of evidence education should be based on and whether science education research can provide the type of evidence required to guide decisions at different levels. This paper argues that theories play a crucial role in building bridges between research and practice. Drawing on literature from science education and the philosophy of science, we contrast the explanatory scope of meta-analyses with the predictive and integrative potential of theories, understood in a structuralist sense as systems of models with defined domains of applicability. We propose that science education research requires both fundamental and applied research, each contributing to theory development at different levels, ranging from local and context-specific models to more fundamental theoretical frameworks. Importantly, we argue that theories in science education should not be viewed merely as applications of psychological or pedagogical theories, but as fundamental theories in their own right. We conclude that the future development of science education research may benefit more from the systematic refinement and integration of theories than from the continued accumulation of isolated local findings, and we propose ways to support the development of such theories. A theory-guided understanding of evidence-based education can strengthen the scientific foundations of the field while simultaneously enhancing its practical relevance, thereby helping to narrow the long-standing theory-practice gap.

Golnoush Abaei, Mojtaba Shahin, Maria Spichkova

The inclusion of internship courses in Software Engineering (SE) programs is essential for closing knowledge gaps and improving graduates' readiness for the software industry. Our study focuses on year-long internships at RMIT University (Melbourne, Australia), which offers in-depth industry engagement. We analysed how the course evolved over the last 10 years to incorporate students' needs and summarised the lessons learned that can be helpful for other educators supporting internship courses. Our qualitative analysis of internship data based on 91 reports during 2023-2024 identified three challenge themes the students faced, and which courses were found by students to be particularly beneficial during their internships. On this basis, we proposed recommendations for educators and companies to help interns overcome challenges and maximise their learning experience.

Viktoriia Makovska, Ihor Michurin, Mariia Tokhtamysh et al.

Entity-Relationship (ER) modeling is commonly taught as a primarily technical activity, despite its central role in shaping how data systems represent people, processes, and institutions. Prior research in participatory design demonstrates that involving diverse stakeholders in modeling can surface tacit knowledge, challenge implicit assumptions, and produce more inclusive data representations. However, database education currently lacks structured pedagogical approaches for teaching participatory ER modeling in practice. We introduce the GARLIC methodology for teaching and learning participatory ER modeling. GARLIC adapts and extends the ONION participatory ER modeling framework of Makovska et al.(HILDA 2025) into a workshop-based learning format that combines role-playing, collaborative synthesis, guided critique, and iterative refinement. GARLIC is designed to develop both technical modeling skills and critical awareness of the social and ethical dimensions of data representation. GARLIC lowers the barrier to participatory ER modeling and equips students with practical skills for collaborative, inclusive data model design.

Lucile Favero, Juan-Antonio Pérez-Ortiz, Tanja Käser et al.

The increasing integration of AI tools in education presents both opportunities and challenges, particularly regarding the development of the students' critical thinking skills. This position paper argues that while AI can support learning, its unchecked use may lead to cognitive atrophy, loss of agency, emotional risks, and ethical concerns, ultimately undermining the core goals of education. Drawing on cognitive science and pedagogy, the paper explores how over-reliance on AI can disrupt meaningful learning, foster dependency and conformity, undermine the students' self-efficacy, academic integrity, and well-being, and raise concerns about questionable privacy practices. It also highlights the importance of considering the students' perspectives and proposes actionable strategies to ensure that AI serves as a meaningful support rather than a cognitive shortcut. The paper advocates for an intentional, transparent, and critically informed use of AI that empowers rather than diminishes the learner.

Suman Saha, Fatemeh Rahbari, Farhan Sadique et al.

This paper explores integrating microlearning strategies into university curricula, particularly in computer science education, to counteract the decline in class attendance and engagement in US universities after COVID. As students increasingly opt for remote learning and recorded lectures, traditional educational approaches struggle to maintain engagement and effectiveness. Microlearning, which breaks complex subjects into manageable units, is proposed to address shorter attention spans and enhance educational outcomes. It uses interactive formats such as videos, quizzes, flashcards, and scenario-based exercises, which are especially beneficial for topics like algorithms and programming logic requiring deep understanding and ongoing practice. Adoption of microlearning is often limited by the effort needed to create such materials. This paper proposes leveraging AI tools, specifically ChatGPT, to reduce the workload for educators by automating the creation of supplementary materials. While AI can automate certain tasks, educators remain essential in guiding and shaping the learning process. This AI-enhanced approach ensures course content is kept current with the latest research and technology, with educators providing context and insights. By examining AI capabilities in microlearning, this study shows the potential to transform educational practices and outcomes in computer science, offering a practical model for combining advanced technology with established teaching methods.

Huixin Gao, Tanya Evans, Anna Fergusson

This scoping review examines the use of student explanation strategies in postsecondary mathematics and statistics education. We analyzed 46 peer-reviewed articles published between 2014 and 2024, categorizing student explanations into three main types: self-explanation, peer explanation and explanation to fictitious others. The review synthesizes the theoretical underpinnings of these strategies, drawing on the retrieval practice hypothesis, generative learning hypothesis, and social presence hypothesis. Our findings indicate that while self-explanation and explaining to fictitious others foster individual cognitive processes enhancing generative thinking, peer explanation have the potential to combine these benefits with collaborative learning. However, explanation to fictitious others have the potential to mitigate some of the negative impacts that may occur in peer explanation, such as more knowledgeable students dominating peer discussions. The efficacy of the methods varies based on implementation, duration, and context. This scoping review contributes to the growing body of literature on generative learning strategies in postsecondary education and provides insights for optimizing the integration of student explanation techniques in mathematics and statistics.

Brittany N. Hupp, Mohammed S. Hashim, Raquel Bryant et al.

Scientific ocean drilling (SciOD) has been invaluable in advancing our understanding of Earth history. However, the most recent international SciOD programme ended in 2024, alongside the non-renewal of the riserless drilling vessel, the JOIDES Resolution. The US has not committed to joining a new SciOD programme despite prior efforts focused on important scientific priorities (e.g. climate change, assessing natural hazards). During this critical juncture, we argue that incorporating accessibility, justice, equity, diversity and inclusion (AJEDI) efforts will further develop a cohesive community that is well prepared to tackle questions critical to the US and global community. Herein we provide recommendations to develop a knowledgeable and diverse community of scientists in the changing landscape of US SciOD, as informed by historical participation data and recent efforts by early career scientists. Recommendations focus on accessible training opportunities, enhanced stewardship of archived materials, additional funding for research at all academic levels, inclusion of cultural advisors and social scientists, and a commitment to continuing SciOD education. By pursuing these recommendations, the US SciOD community could become a leader for modelling AJEDI principles and ensuring equitable knowledge transfer that is needed to reimagine and rebuild a new, inclusive SciOD programme.

Katayoun Katebi, Saba Yazdanian Asr, Zeinab Mahboobi et al.

Abstract Introduction Recurrent aphthous stomatitis (RAS) is one of the most prevalent oral inflammatory ulcerative lesions, characterized by painful ulcers that develop on non-keratinized oral mucosa, significantly affecting the quality of life. This study aimed to evaluate the prevalence of RAS and its associated risk factors within the Azar cohort population. Methods This cross-sectional study utilized data from the Azar cohort, which has been ongoing since 2014 in Shabestar City, East Azarbaijan, Iran, involving 15,006 adults aged 35 to 70 years. To assess the prevalence of RAS, participants were provided with a description of these lesions and asked whether they had ever experienced RAS in the oral cavity. Data collection was based on self-reports and examinations conducted by the physicians involved in the Azar cohort. Participants with RAS were classified into the RAS group, while the remaining participants were categorized into the non-RAS group. We assessed the association between RAS and various factors using binary logistic regression. Results In the study population, there were 3,503 individuals in the RAS group and 11,503 individuals in the non-RAS group. The prevalence of RAS in the Azar cohort was 23.34%. Individuals over 50 years of age (p < 0.001), those with a poor (p < 0.001) or very poor (p = 0.02) socio-economic status, a low educational level (p = 0.01), smokers (p < 0.001) and individuals with a history of smoking who have since quit (p = 0.01) were significantly less affected by RAS. Conversely, individuals with genital aphthous lesions (p < 0.001), depression (p < 0.001), rheumatoid disease (p = 0.01), and food allergies (p < 0.001) were significantly more affected by RAS. Conclusions Factors such as being under 50 years of age, possessing a high socioeconomic status, having a higher level of education, experiencing genital aphthous disease, suffering from depression, having rheumatoid disease, and having food allergies may be associated with a higher prevalence of RAS.

Carlos Pérez Wic, Pablo Cavero López, Elvira Rodríguez Tenorio et al.

El creciente impacto de la inteligencia artificial (IA) en los entornos educativos hace necesario comprender cómo su implementación influye en la satisfacción laboral del profesorado, especialmente cuando intervienen factores personales que pueden modular dicha experiencia. En este marco, el estudio se plantea analizar de qué manera variables sociodemográficas como el género y la edad condicionan la satisfacción laboral docente asociada al uso de IA, atendiendo a posibles diferencias en la forma en que el profesorado percibe e incorpora estas tecnologías en su práctica diaria. Para ello, se aplicó un cuestionario a 51 docentes con el fin de comparar las percepciones entre hombres y mujeres e identificar posibles diferencias según distintos rangos de edad. El análisis confirma diferencias significativas según el género, siendo los hombres quienes reportan mayor satisfacción, mientras que la edad no constituye un factor determinante. Este estudio evidencia la necesidad de políticas formativas inclusivas que reduzcan brechas y favorezcan una integración equilibrada de la IA en la práctica docente.

Jun-ichiro Yasuda, Michael M. Hull, Naohiro Mae et al.

Although conceptual assessment tests are commonly administered at the beginning and end of a semester, this pre-post approach has inherent limitations. Specifically, education researchers and instructors have limited ability to observe the progression of student conceptual understanding throughout the course. Furthermore, instructors are limited in the usefulness of the feedback they can give to the students involved. To address these challenges, we propose an alternative approach that leverages computerized adaptive testing (CAT) and increasing the frequency of CAT-based assessments during the course, while reducing the test length per administration, thus keeping or decreasing the total number of test items administered throughout the course. The feasibility of this idea depends on how far the test length per administration can be reduced without compromising the test accuracy and precision. Specifically, the overall test length is desired to be shorter than when the full assessment is administered as a pretest and subsequent post-test. To achieve this goal, we developed a CAT algorithm that we call Chain-CAT. This algorithm sequentially links the results of each CAT administration using collateral information. We developed the Chain-CAT algorithm using the items of the Force Concept Inventory (FCI) and analyzed the efficiency by numerical simulations. We found that collateral information significantly improved the test efficiency, and the overall test length could be shorter than the pre-post method. Without constraints for item balancing and exposure control, simulation results indicated that the efficiency of Chain-CAT is comparable to that of the pre-post method even if the length of each CAT administration is only 5 items and the CAT is administered 9 times throughout the semester. (To continue, see text.)

Federico Lazarín Miranda

La propuesta de Dossier se denomina Temas, problemas y enfoques regionales de la educación, siglos XIX y XX, es el resultado de la discusión y presentación de avances de investigación de los miembros del Seminario de Historia Mundial: “Temas, problemas y enfoques tradicionales y actuales de la educación, siglos XIX-XXI” que se lleva a cabo en la Universidad Autónoma Metropolitana Iztapalapa desde el año 2021.

Ana Carolina Tomé Klock, Brenda Salenave Santana, Juho Hamari

Gamification is a technological, economic, cultural, and societal development toward promoting a more game-like reality. As this emergent phenomenon has been gradually consolidated into our daily lives, especially in educational settings, many scholars and practitioners face a major challenge ahead: how to understand and mitigate the unethical impacts of gamification when researching and developing such educational technologies? Thus, this study explores ethical challenges in gamified educational applications and proposes potential solutions to address them based on an umbrella review. After analysing secondary studies, this study details and proposes recommendations on addressing some ethical challenges in gamified education, such as power dynamics and paternalism, lack of voluntarity and confidentiality, cognitive manipulation, and social comparison. Research and development decision-making processes affected by such challenges are also elaborated, and potential actions to mitigate their effects in gamification planning, conducting and communication are further introduced. Thus, this chapter provides an understanding of ethical challenges posed by the literature in gamified education and a set of guidelines for future research and development.

Teklemariam Ergat Yarinbab, Hailay Abrha Gesesew, Margo Shawn Harrison et al.

Abstract Ethiopia has implemented maternity waiting homes over the last several decades; however, its utilization is low. This study aimed to assess the factors associated with knowledge of and attitude towards maternity waiting homes among pregnant women in rural Ethiopia. The baseline survey was conducted from September 15 to October 30, 2022, in rural Southern Ethiopia. Survey data were collected from 320 women in their second trimester of pregnancy. The data analysis was performed using SPSS version 25. The mean age of the participants was 27.79 (SD ± 6.242) years. Nearly two-thirds (57.5%) of the participants had no formal education and more than three-fourths (72.5%) were housewives. Only approximately one-fourth (23.75%) of the participants used maternity waiting homes. Furthermore, 33.75% had good knowledge, 28.75% had favorable attitudes, and around one-fourth (26.25%) had good male partner involvement. Age group 30 to 39 years (AOR 4.78, 95% CI 1.12–20.36), household income (AOR 6.41, 95% CI 2.78–14.81), having pregnancy intention (AOR 2.63, 95% CI 1.21–5.73), and history of obstetric complications (AOR 6.72, 95% CI 2.81–16.07) were significantly associated with good knowledge about maternity waiting homes. Similarly, age group 30 to 39 years (AOR 4.23, 95% CI 1.14–15.65), household income (AOR 7.12, 95% CI 3.26–15.55), having pregnancy intention (AOR 2.57, 95% CI 1.21–5.47), and history of obstetric complications (AOR 5.59, 95% CI 2.30–13.59) were significantly associated with favorable attitudes towards maternity waiting homes. Providing health education and promoting male partner participation through educating couples may improve women’s access to maternity waiting homes.

Mohammad Asadi, Vinitra Swamy, Jibril Frej et al.

Time series is the most prevalent form of input data for educational prediction tasks. The vast majority of research using time series data focuses on hand-crafted features, designed by experts for predictive performance and interpretability. However, extracting these features is labor-intensive for humans and computers. In this paper, we propose an approach that utilizes irregular multivariate time series modeling with graph neural networks to achieve comparable or better accuracy with raw time series clickstreams in comparison to hand-crafted features. Furthermore, we extend concept activation vectors for interpretability in raw time series models. We analyze these advances in the education domain, addressing the task of early student performance prediction for downstream targeted interventions and instructional support. Our experimental analysis on 23 MOOCs with millions of combined interactions over six behavioral dimensions show that models designed with our approach can (i) beat state-of-the-art educational time series baselines with no feature extraction and (ii) provide interpretable insights for personalized interventions. Source code: https://github.com/epfl-ml4ed/ripple/.

Heiko Dietrich, Tanya Evans

Traditional lectures are commonly understood to be a teacher-centered mode of instruction where the main aim is a provision of explanations by an educator to the students. Recent literature in higher education overwhelmingly depicts this mode of instruction as inferior compared to the desired student-centered models based on active learning techniques. First, using a four-quadrant model of educational environments, we address common confusion related to a conflation of two prevalent dichotomies by focusing on two key dimensions: (1) the extent to which students are prompted to engage actively and (2) the extent to which expert explanations are provided. Second, using a case study, we describe an evolution of tertiary mathematics education, showing how traditional instruction can still play a valuable role, provided it is suitably embedded in a student-centered course design. We support our argument by analyzing the teaching practice and learning environment in a third-year abstract algebra course through the lens of Stanislav Dehaene's theoretical framework for effective teaching and learning. The framework, comprising "four pillars of learning", is based on a state-of-the-art conception of how learning can be facilitated according to cognitive science, educational psychology, and neuroscience findings. In the case study, we illustrate how, over time, the unit design and the teaching approach have evolved into a learning environment that aligns with the four pillars of learning. We conclude that traditional lectures can and do evolve to optimize learning environments and that the erection of the dichotomy "traditional instruction versus active learning" is no longer relevant.

Heidi Brattland, Katrine Høyer Holgersen, Patrick A Vogel et al.

<h4>Background</h4>One approach towards advancing the quality of mental health care is to improve psychotherapists' skills through education and training. Recently, psychotherapy training has benefitted from adapting training methods from other professions (e.g., deliberate practice). The apprenticeship model has a long history in skill trades and medicine, but has yet to be adopted in training mental health professionals. This study aims to investigate the impact of apprenticeship training on clinical psychology students' skills.<h4>Methods</h4>In a pragmatic mixed-methods trial, 120 first year students in a Master's degree clinical psychology program will be randomized to either training-as-usual or training-as-usual plus psychotherapy apprenticeship. In the intervention group, students will participate, over a period of 10 weeks, in weekly treatment sessions together with licensed therapists at outpatient mental health and substance use treatment clinics. Outcomes are assessed post-intervention and at two-year follow-up. The main outcome measure is the Facilitative Interpersonal Skills (FIS) performance test. Additional self-report measures tap self-efficacy, self-compassion, worry, rumination, and stress. Weekly reflection log entries written by the students will be qualitatively analyzed in order to gain an in-depth understanding of the learning process. Students' and therapists' experiences with the intervention will be explored in focus group interviews.<h4>Discussion</h4>To the best of our knowledge, this is the first controlled study to investigate the impact of apprenticeship as an isolated training component in the education of clinical psychologists. The study is designed so as to yield a comprehensive understanding of an approach which could prove to be a valuable supplement to the existing educational methods in this field and ultimately, contribute to improve the quality of mental health care.

Laila Sari, Marjono Marjono, Sumardi Sumardi et al.

Perwujudan nasional merupakan langkah utama yang dilakukan oleh Orde Baru pada masa pemerintahannya (1966-1998). Perwujudan budaya nasional di bidang kebudayaan dilakukan dengan karya sastra yang bertentangan dengan nasional. Tujuan dari penelitian ini adalah untuk mengetahui latar belakang, implementasi dan dampak dari kebijakan pelarangan karya sastra. Penelitian ini menggunakan metode penelitian sejarah dan pendekatan institusionalisme politik. Hasil penelitian menunjukkan bahwa latar belakang pelarangan karya sastra adalah munculnya resistensi kebijakan sastra. Implementasi kebijakan pelarangan karya sastra berupa pelarangan buku sastra dan tersingkirkan pengarang. Kata Kunci : Orde Baru, Karya Sastra, Literasi.

Anna Duda, Anna Mróz, Małgorzata Mądry-Kupiec et al.

Rola mediatora rówieśniczego jest wymagająca zarówno pod względem emocjonalnym, jak i intelektualnym dla ucznia, który się jej podejmuje. Konieczne zatem wydaje się diagnozowanie dzieci i młodzieży pod kątem posiadanych predyspozycji mediacyjnych. Autorki za pomocą autorskiego narzędzia, wyróżniając pięć podstawowych kategorii predyspozycji, poddały diagnozie uczniów szkół podstawowych w wieku 11–13 lat. Diagnoza predyspozycji służy przede wszystkim określeniu kierunku pracy z młodzieżą kandydującą do roli mediatorów i stanowi punkt wyjścia do rozwijania ich kompetencji mediacyjnych. Ponadto zebrane wyniki wskazują na mocne strony, jak i na deficyty w obszarach rozwojowych i poznawczych istotnych w kontekście mediacji. Analiza danych wskazała także na możliwe wystąpienie zależności między skutkami pandemii a obniżeniem się poziomu predyspozycji mediacyjnych, głównie umiejętności społecznych i emocjonalnych, które wymagają treningu umiejętności skutecznego nawiązywania relacji interpersonalnych.