Hasil untuk "Theory and practice of education"

Jonathan Graves

In this paper, I discuss a fundamental problem for most instructors: how should we weight the different assessments within our course in order to evaluate students effectively? Using a framework which connects curriculum and assessment design, I demonstrate that “fair” evaluation requires a close (and quantitatively measurable) connection between learning outcomes and assessment weighting. I use this framework to provide guidance for optimal assessment design practices, and evaluate a number of commonly-used teaching practices – concluding that many of them pose problems in terms of fairness, when not carefully implemented. I also discuss the implications of alternative grading schemes or other complications for this framework. I finally provide a detailed example of applying these principles to a real-world course, and a toolkit, for use by instructors in evaluating or designing their own courses.

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.

Omer Sami Kaya, Erinç Erçağ

Despite the growing attention towards gamification in learning context, challenge-based gamification application has rarely been subjected to testing in education. In recognition of this void, and grounded on gamification principles, we developed Educhall web-based program. Drawing on self-determination theory, and flow theory the present study aims to explore how the application of this challenge-based gamified program in to learning process of students can increase students’ motivation, flow, and academic success through the generated competition and challenge. The study applied a random experimental research design within distance learning context with 30 university students of control group and 30 students of experimental group who used the Educhall application for one academic semester. In line with self-determination theory, it was statistically evidenced that application of challenge-based gamified learning method increased level of academic performance and overall motivation. Of the motivational sub factors, experimental group reported significantly higher confidence level and satisfaction towards the course. Furthermore, grounded on flow theory, the study showed that challenge-based gamified learning increased flow level of learners but not significantly which warrants further data collection and experimental research in future studies. Implications for research and practice are discussed.

Angel M. Y. Lin

ABSTRACT Translanguaging theories emphasize a fluid, dynamic view of language and differ from code-switching/mixing theories by de-centring the analytic focus from the language(s) being used in the interaction to the speakers who are making meaning and constructing original and complex discursive practices. Trans-semiotizing theories further broaden the focus to analyse language as entangled with many other semiotics (e.g. visuals, gestures, bodily movement) in meaning making. In this paper recent developments in trans/languaging and trans-semiotizing theories are discussed in conjunction with fine-grained classroom analyses to illustrate the key role played by trans/languaging and trans-semiotizing practices in the dialogic construal of content meaning in content-based education.

Oleksandr Tymoshchuk

The expansion of nuclear technologies in various industries, combined with the constant threat of radiation-related incidents, highlights the urgent need for effective radiation education. This study is devoted to an empirical investigation of the effectiveness of artificial intelligence tools (neurological models of artificial intelligence) in detecting and correcting of artificial intelligence tools (neurological models of artificial intelligence) in detecting and correcting misconceptions about radiation (ionising radiation). We empirically evaluate the effectiveness of artificial intelligence (AI) tools in detecting and correcting these misconceptions among university students, focusing on different cognitive, cognitive-activity, and systemic-axiological levels. A pedagogical experiment was conducted with 168 students of Ukrainian universities using control questionnaires to assess the effectiveness of the selected artificial intelligence tools. The experiment involved presenting students with a series of statements designed to identify misconceptions related to factual knowledge (e.g., radiation units, background levels), conceptual understanding (e.g., the difference between radiation and radioactivity, effects of low-dose exposure), and application/evaluation (e.g., risk assessment, protective measures). AI tools, including natural language processing models for text analysis and machine learning algorithms for misconceptions classification, were used to provide personalised feedback and targeted corrective information. The results show that AI achieved high accuracy (80-98%) in eliminating misconceptions about factual knowledge. However, the effectiveness decreased for misconceptions requiring deeper conceptual understanding (73-78%) and is much lower for those involving complex knowledge assessment and application (24-36%). These findings indicate that while AI has significant potential to improve basic radiation literacy and provide automated feedback, its current capabilities are limited in addressing more multidimensional and complex misconceptions. Further research is needed to develop more sophisticated AI-based integrations that can effectively target higher-order cognitive skills and promote a more complete understanding of radiation science and its implications. This study contributes to this field by providing empirical evidence on the strengths and weaknesses of AI in radiation education, and offers practical recommendations for the further development and implementation of customised AI-based learning tools.

Michael Fitzgerald, Rachel Freed, Dan Reichart et al.

As astronomy enters an era defined by global telescope networks, petabyte-scale surveys, and powerful computational tools, the longstanding goals of astronomy education, particularly introductory ``ASTRO101'', but equally encompassing both higher and lower level courses, warrant fresh examination. In June 2024, the AstroEdUNC meeting at UNC--Chapel Hill convened 100 astronomers, education researchers, and practitioners to synthesise community perspectives on the purpose, content, and delivery of astronomy education. Beginning with historical vignettes, the meeting's deliberations were organised into six interrelated themes: (1) Context, highlighting astronomy's evolution from classical charting to multi-messenger discovery and its role as a connective thread across STEM and the humanities; (2) Content, exploring how curricula can balance essential concepts with authentic investigations and leverage open-source and AI-augmented resources; (3) Skills, arguing that astronomy should foreground scientific literacy, computational fluency, and communication through genuine data-driven inquiry; (4) Engagement, advocating for active-learning strategies, formative assessment, and culturally inclusive narratives; (5) Beyond the Classroom, emphasising scaffolding, universal-design practices, and K--12/community partnerships; and (6) Astronomy Education Research, outlining priority areas for assessing knowledge, attitudes, and long-term outcomes. We provide concrete recommendations for future astronomy education research development, underscoring the need for approaches to education that are authentic while meeting the learning and life goal needs of the students, a vibrant community of practice and robust researcher-practitioner partnerships to ensure that introductory astronomy is pertinent, applicable and inspiring to a broad student population.

Veronika Hackl, Alexandra Mueller, Maximilian Sailer

The integrative literature review addresses the conceptualization and implementation of AI Literacy (AIL) in Higher Education (HE) by examining recent research literature. Through an analysis of publications (2021-2024), we explore (1) how AIL is defined and conceptualized in current research, particularly in HE, and how it can be delineated from related concepts such as Data Literacy, Media Literacy, and Computational Literacy; (2) how various definitions can be synthesized into a comprehensive working definition, and (3) how scientific insights can be effectively translated into educational practice. Our analysis identifies seven central dimensions of AIL: technical, applicational, critical thinking, ethical, social, integrational, and legal. These are synthesized in the AI Literacy Heptagon, deepening conceptual understanding and supporting the structured development of AIL in HE. The study aims to bridge the gap between theoretical AIL conceptualizations and the practical implementation in academic curricula.

Gahyoun Gim, Jinhyuk Yun, Sang Hoon Lee

We propose a framework to quantify and utilize interdisciplinarity in science and engineering curricula at the university-level higher education. We analyze interdisciplinary relations by standardizing large-scale official educational data in Korea using a cutting-edge large language model and constructing knowledge maps for disciplines of scientific education. We design and evaluate single-field and integrated dual-field curricula by adapting pedagogical theory and utilizing information theory-based metrics. We develop standard curricula for individual disciplines and integrated curricula combining two fields, with their interdisciplinarity quantified by the curriculum synergy score. The results indicate higher interdisciplinarity for combinations within or across closely related fields, especially in engineering fields. Based on the analysis, engineering fields constitute the core structure of our design for curriculum interdisciplinarity, while basic natural science fields are located at peripheral stems to provide fundamental concepts.

Pierangela Bruno, Carmine Dodaro, Giuseppe Galatà et al.

The Operating Room Scheduling (ORS) problem deals with the optimization of daily operating room surgery schedules. It is a challenging problem subject to many constraints, like to determine the starting time of different surgeries and allocating the required resources, including the availability of beds in different department units. Recently, solutions to this problem based on Answer Set Programming (ASP) have been delivered. Such solutions are overall satisfying but, when applied to real data, they can currently only verify whether the encoding aligns with the actual data and, at most, suggest alternative schedules that could have been computed. As a consequence, it is not currently possible to generate provisional schedules. Furthermore, the resulting schedules are not always robust. In this paper, we integrate inductive and deductive techniques for solving these issues. We first employ machine learning algorithms to predict the surgery duration, from historical data, to compute provisional schedules. Then, we consider the confidence of such predictions as an additional input to our problem and update the encoding correspondingly in order to compute more robust schedules. Results on historical data from the ASL1 Liguria in Italy confirm the viability of our integration. Under consideration in Theory and Practice of Logic Programming (TPLP).

Zohaib Hasan Sain

This study aims to identify effective forms of parental involvement in fostering teachers' emotional well-being and to explore its implications for educational policy. The research employs a qualitative approach with a case study method conducted at elementary schools at Lahore. Data collection techniques include in-depth interviews, participatory observations, and document analysis. The findings indicate that emotional support in parental involvement, contributions of parental involvement to enhancing teachers' job satisfaction, and parental participation in school activities as a support for teachers' emotional well-being play crucial roles in supporting teachers' emotional welfare. Recognition and appreciation of parental involvement were also found to be significant motivational factors. This research contributes by reinforcing the understanding of the importance of synergy between schools, parents, and the community in creating a positive and supportive learning environment. However, the study is limited to a single location and does not account for broader variations in gender and age. Therefore, further research is needed to obtain a more comprehensive perspective and to support more targeted educational policy-making.

Stefanie Lenzer, Laura Pannullo, Andreas Nehring et al.

Scientific literacy, a central goal of modern science education, should be accessible to all students regardless of their backgrounds. Despite international education reforms focused on diversity, equity and inclusion many teachers struggle to create inclusive science lessons. One reason may be, that creating inclusive science lessons is challenging: it requires teachers to balance the demands of science education with the diverse needs of their students. Therefore, teachers need support in planning inclusive science lessons. To address this issue, members of a German network for inclusive science education (Netzwerk inklusiver naturwissenschaftlicher Unterricht, NinU) have developed the NinU framework. This framework integrates perspectives from both science education and inclusive pedagogy to support teachers in planning and reflecting inclusive science lessons. Originally created as a workshop resource for the NARST 2023 conference, this self-study manual provides 1) an overview of the theory behind the NinU framework, 2) examples and 3) exercises for acknowledging diversity, recognizing barriers and enabling participation using the framework.

Pylyp Kuznietsov, Igor Girka, Igor Kyryllin et al.

This article provides the description of current training processes and structure of education in quantum physics at the Education and Research Institute "School of Physics and Technology" (SPT) of V.N. Karazin Kharkiv National University, Ukraine. Crucial feature of quantum education at the SPT is the involvement of scientists and experts from national and international research centers who are actively working in the field. By taking example of particular quantum courses, we outline the main challenges in the educational process during the large-scale military aggression and the ways the lecturers, scientific employees, and students manage to overcome them. We also overview the recently emerged initiatives oriented on sustaining and development of quantum education in Kharkiv, as well as the international events with a broader impact. History of the School and its main achievements are provided in brief.

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.)

M. Tayade, R. G. Latti

Early clinical exposure (ECE) is a teaching-learning methodology which fosters the exposure of medical students to the patients as early as the first year of medical college. A worldwide number of research studies investigated the outcome of ECE and found, ECE sessions motivate the medical student in various ways making their academic strength, improve clinical skills, and improve communication skills and making them more confident. In the medical curriculum, ECE makes an overall impact on student's performance and confidence. Planning of ECE in real-time practices can be done in different settings with the use of appropriate resources such as logbook, textbooks, notes, instruments, learning material, case record sheets, and computers. Herewith, we reviewed the scientific base responsible for these outcomes and discussed different ECE settings and their outcome. The Medical Council of India in new educational reforms made ECE sessions compulsory from 2019 in undergraduate medical curriculum. In conclusion, the challenge for health professions education is to look for ways to improve the quality of clinical education by comparing students’ understanding and modifying practices of clinical education in new circumstances. Early clinical experience will definitely play a crucial role in this context, only if proper strategies are implemented. This systemic review article highlights ECE settings and scientific basis in a theoretical way helpful for medical faculties during its implementation in regular teaching.

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.

AVOTT National Coordination of Open Science and Research

This Policy for Open Access to Research Data and Methods supports the Declaration for Open Science and Research 2020–2025 and its overarching principle that research should be as open as possible and as closed as necessary. This policy builds on extensive national and international work and dialogue. It has been drawn up by the Finnish research community and coordinated by National Coordination for Open Science and Research (the Federation of Finnish Learned Societies).  The policy focuses on the openness of research data, methods, and infrastructures. It views openness as an element of research quality and impact across the full life cycle of research and as an opportunity to advance global inclusivity in research. It considers research data and methods as independent research outputs, and generally encourages opening up the research process as early and widely as possible, and requests that limitations to openness should be justified. Existing frameworks, such as the FAIR principles, can be used to regulate the level of openness for research data and various types of methods.  All fields of higher education and research are covered by this policy. The diversity across fields forms challenges for translating and implementing best practices. The policy emphasises general principles of responsible management of research resources, access to appropriate services, and responsible research evaluation. These guiding principles have been formulated as specific objectives and actions for researchers, research and funding organisations, and other actors. The Open Science Coordination at the Federation of Finnish Learned Societies will monitor the implementation and further development of this policy as part of the national open science monitoring programme.

Magda Cristina TUNEGARU

In this paper, we aim to examine intercultural education textbooks, a subject that has been introduced in Romania, in the new school curriculum for middle school in 2017, for the 6th grade. The research uses content analysis to identify and analyze the cultural topics, the types of interactions that are suggested, and the extent to which these textbooks address social justice issues. We will approach both the textual and the visual elements of the textbooks. The data is analyzed on four levels, using a social justice perspective, mainly Iris Young’s conceptualization of oppression. First, we explore the micro level which refers to the characters’ attitudes and values; then the macro level which comprises historical and political factors. Further, we examine the international dimension comprised in the analyzed textbooks. Finally, we are interested in the authors’ position. For this purpose, we employ Hilliard’s (2014) conceptual frameworks, developed from Gray (2010) – to which we added 12 topics – and Risager (1991). Moreover, the research proposes further analysis and inquiries on the subject of intercultural education in Romania.

Cinematographers are trained to control and measure the relative difference in brightness between two parts of a scene, or a face, for expressive purposes. Painting is often referred to for inspiration as practitioners learn to compose and represent light and shadow in an aesthetically considered manner. In this respect, it is noteworthy that the painters generally studied by film-making students are mostly from Renaissance traditions and produced work featuring predominantly White models. This gap of racial representation in cinematographic pedagogy is stark and has long been overlooked. This article mounts an enquiry into the lack of diversity in cinematography education, examining how different aesthetic traditions, such as Asian ink paintings, could pave new ways for decolonising the conventional conceptions of lighting ratios. Drawing on qualitative and quantitative case studies undertaken in university workshops, I discuss how students respond to Black and Asian artwork as visual references when they are tasked with lighting models with non-White skin tones to accommodate the different reflectance of their skins. By comparing the learning outcomes and current industry techniques for optimising screen representation of Black, Asian and minority ethnic groups, the article evaluates how students respond to learning from modern artwork that promotes diverse identities, and argues for the benefits of integrating greater inclusiveness into cinematography.

Alicja Syska

Peer reviewing is unquestionably the cornerstone of scholarly activity. It is universally seen as one of the very few ways we have to ensure that what gets published has been subjected to rigorous scrutiny by peers. Entering into this dialogue with other experts in the field is of tremendous benefit to authors, even if it hurts sometimes. But it is also so much more than that: peer reviewing helps us develop our own research and thinking capabilities, improve our criticality, and hone the skill of providing constructive feedback. Peer reviewing is an act of service that makes us a better, stronger, and more resilient academic community. Like all acts of service, it relies on the good that is in us: being generous with time and personal resources, being committed to helping others, having a sense of reciprocal responsibility, feeling a constant desire to learn, and being open to dialogic exchange with authors and editors. I believe it is this dialogic exchange that brings us together as a community. As Co-Lead Editor of the Journal of Learning Development in Higher Education (JLDHE), the questions I was interested in exploring included: • How do we ensure that every voice feels valued in peer review? • How do we encourage sharing diverse perspectives to achieve better publishing outcomes? • How do we attract peers to reviewing and use their goodwill to build a strong, proud, and sustainable scholarly community in learning development?

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/.