Search Results (84)

The rapid integration of digital technologies into education has transformed electronic textbooks (e-textbooks) from static replicas of printed books into interactive, multimedia-rich learning environments. This bibliometric literature review synthesizes findings from 89 peer-reviewed studies published between 2000 and 2024, retrieved from IEEE Xplore, ACM Digital Library, ScienceDirect, and SpringerLink. Following the Kitchenham and Charters methodology and complemented by bibliometric analyses, this review is guided by the overarching research question (RQ): How are e-textbooks conceptualized, designed, and deployed to support learning outcomes while promoting accessibility and equity? This guiding question is complemented by three additional RQs: (1) How has the field of e-textbooks developed over time? (2) Which countries are leading research related to interactive textbooks, considering quantitative indicators of publications/country? (3) What evidence exists regarding the contribution of e-textbooks to learning outcomes? The analysis reveals a clear trajectory from early static digitization toward intelligent platforms incorporating adaptive feedback, personalization, and analytics. Well-designed e-textbooks using multimedia learning principles demonstrate significant potential to enhance conceptual understanding, learner engagement, and motivation—especially in K–12 contexts. However, the field remains challenged by definitional inconsistencies, the uneven application of accessibility standards, and the geographic concentration of research output in North America and East Asia. These disparities highlight an urgent need to align digital textbook development with broader global education goals. By foregrounding accessibility, inclusion, and equitable access, e-textbooks can play a transformative role in advancing Sustainable Development Goal 4 (Quality Education) by ensuring inclusive, engaging learning opportunities, and SDG 10 (Reduced Inequalities) by reducing educational disparities across diverse learner populations. This review concludes by calling for interdisciplinary frameworks that integrate cognitive science, human–computer interaction, and artificial intelligence to guide the design of the next generation of interactive, accessible, and pedagogically robust e-textbooks—tools that are not only technologically innovative, but also aligned with global commitments to equitable and sustainable education for all. Full article

We introduce a single dimensionless landscape function $J_{\mathrm{chem}}\left(\rho \right)=cosh(\rho ln\phi )-1$, with $\phi =(1+\sqrt{5})/2$, defined on the noble gas-centred coordinate $\rho =d/L_p\in [0,1)$, and show that it organizes four central within-period atomic observables, first ionization energy ${\mathrm{IE}}_1$, electron affinity $\mathrm{EA}$, Mulliken electronegativity ${\chi }_M$, and Pearson chemical hardness $\eta$, on a single periodic-table axis. The outward step $\Delta J_{\mathrm{chem}}^{+}$ delivers ${\mathrm{IE}}_1$, the inward gap $\Delta J_{\mathrm{chem}}^{-}=J_{\mathrm{chem}}\left(1\right)-J_{\mathrm{chem}}\left(\rho \right)$ delivers $\mathrm{EA}$ and $\eta$, and ${\chi }_M$ follows from Mulliken’s identity. Benchmarked against NIST and Pearson tabulated atomic data, the framework reproduces the within-period ${\mathrm{IE}}_1$ envelope across periods 2–6 and localizes every upward deviation on the textbook anomaly sites $\{p^3,d^5,f^7,s^2,d^{10}\}$; it yields two parameter-free golden ratio ionization-energy identities (${\phi }^{1/4}$ on heavy noble gas pairs and ${\phi }^2$ on halogen/alkali pairs, agreeing with data to MAD $\approx 1\%$ and $\approx 5\%$); and it provides single-parameter analytical fits for $\mathrm{EA}$ (MAE $0.3$–$0.4$ eV), Pearson hardness $\eta$, and Mulliken ${\chi }_M$ ($R^2=0.73$ on a 15-atom 4-class benchmark). By assembling four periodic-table observables under one golden ratio cosh coordinate, the construction provides a compact analytical reference against which relativistic and shell-anomaly corrections can be quantified. Full article

Background: Debate continues to swirl around the effectiveness of novel nicotine-delivery products such as snus and e-cigarettes as tobacco cessation aids. The purpose of this review is to quantify the state of research on modern products, including e-products, and established or developing pharmaceuticals on assisting nicotine users in achieving cessation. Methods: This study relied on a comprehensive assessment of research articles, clinical trials, drug approvals, and textbook material available via PubMed, Ovid Wolters Kluwer, and Wiley. We utilized Python 3.14.2, Anaconda3, the ShinyWeb App, and Py.Litstudy to investigate the selected literature. Our key study elements are product evolution and cessation behavior associated with e-cigarettes, snus, nicotine gum, nicotine dermal patches, bupropion, varenicline, and cytisine. Results: This manuscript assessed 144 manuscripts published between 1952 and 2025. E-cigarettes and snus, while containing some limited cessation benefit, were not identified to be effective enough at attaining cessation (when used exclusively) to be prescribed as cessation tools. Cytisine was identified as having very similar cessation outcomes to established pharmaceuticals such as varenicline. Conclusions: Since their iteration, e-cigarettes and snus products were marketed as cessation aids. This review found that there is scant evidence to support that modern snus and e-cigarette products work as cessation aids when used in exclusion of other more traditional approaches to cessative aid. Additionally, more modern pharmaceuticals such as cytisine may have benefit as solo cessation tools over novel nicotine-delivery products. Full article

The current study examined the perceptions of elite high school students in the United Arab Emirates about their experiences in learning and acquiring mathematical concepts and skills through the ALEKS system that stands for Assessment and Learning in Knowledge Spaces. ALEKS is an e-assessment and tutoring platform that facilitates the teaching and learning of mathematics for students in Grades 5–12 using versatile and personalized teaching functions. Eight participants of equally mixed gender participated in the study, four Grade 9 and four Grade 10 students. A qualitative research design in the form of one-to-one semi-structured interviews was used to have a deeper understanding of students’ ALEKS experiences, identify the challenges encountered while studying with it, and pinpoint the benefits and advantages of using ALEKS. Results showed that participating students frequently used ALEKS because of two main factors, including rewards promised by teachers and immediate feedback and feeling of immediate achievement provided by the platform. Challenges related to ALEKS were language barriers among the Arabic-speaking students studying in English, a lack of human interaction and support, time management issues, and the necessity for supplementary resources. Multiple advantages were also found, most noticeably how the ALEKS individualized adaptive learning environment helped participants gain more knowledge of mathematical concepts and develop their mathematics skills. Recommendations for mathematics teachers and policymakers include allowing students to utilize ALEKS in small groups in school, aligning ALEKS themes and topics with textbooks learning goals and objectives, giving systematic and personal guidance for increased independent use at home, and making bilingual editions and Arabic-language assets (e.g., tutorial videos) available. Full article

Background: Large language models (LLMs) are being used by surgeons for education and reference yet concerns about hallucinations and reliability limit safe adoption. Retrieval-augmented generation (RAG) can offer a potential solution by grounding responses in a high-quality external database (e.g., medical textbooks) to enhance accuracy. However, performance tradeoffs across different RAG configurations—many of which exponentially increase computational cost—remain poorly characterized. Methods: In total, 120 lightweight, open-source RAG configurations were evaluated across 40 plastic surgery-focused question-answering tasks (20 single-hop, 20 multi-hop), spanning multiple subspecialties (4800 total evaluations). Configurations varied by base LLM (Phi-3-mini-128k-instruct vs. BioMistral-7B), embedding model, database size, chunk size, and query hop type. Performance was assessed using semantic similarity (Ragas) to physician-validated reference answers. Performance was analyzed using linear mixed-effects regression with query as a random effect and fixed and interaction effects selected via likelihood testing and AIC. Results: High performance was achievable using lightweight, open-source models. While BioMistral-7B had high mean sematic similarity under specific configurations (mean semantic similarity up to 0.786), Phi-3-mini-128k-instruct demonstrated more consistent performance across query complexity. Larger database sizes significantly improved semantic similarity, with the largest gain at intermediate sizes (e.g., size 5: +0.043, p = 0.001). Embedding choice had a strong effect, with bge-large-en-v1.5 improving performance (p = 0.0016) and Bio_ClinicalBERT markedly reducing it (p < 0.001). Multi-hop queries substantially reduced performance (p < 0.001), though this effect was attenuated for Phi-3-mini-128k-instruct via a strong model × hop-type interaction (p < 0.001). Conclusions: RAG systems for plastic surgery do not require large proprietary models, as performance depends on configuration choices and interaction effects rather than isolated components. With advancements, predictive modeling may enable resource-efficient, safe deployment of clinical RAG systems. Full article

On one hand, the University of Kragujevac, Serbia, needs an ESP course in ecology; on the other hand, the available wordlists do not meet fully meet the needs of the target group of students, i.e., the undergraduate ecology students. This discrepancy served the a main incentive for creating an institution-specific word list of key content words found in a corpus compiled from English-medium textbooks intended for ecology students (here referred to as the Eco-Text corpus). The keyword list was generated in AntConc, with a keyness measure threshold automatically set at p < 0.055 (3.84 with Bonferroni correction). After the list was complete, the NGSL (New General Service List), NAWL (New Academic Word List), and the SWL (Science Word List) Highlighters were used to further systemize the words into four sublists. In addition to presenting some key findings, we also suggest areas for further refinement. Although preliminary, the findings can be useful to practitioners in planning an ESP course in ecology and developing materials. Full article

Lesson preparation plays a crucial role in structuring and organizing the teaching process. However, traditional lesson design and presentation creation require teachers to spend a considerable amount of time reviewing the literature and organizing materials. Therefore, developing an intelligent and multimodal technology capable of automatically generating lesson materials holds great significance. Such technology can potentially reduce teachers’ workloads and improve the efficiency and quality of lesson preparation, as indicated by teacher satisfaction and preference judgments. In this paper, we introduce LessonAgent, a multimodal and interactive pipeline that leverages large language models (LLMs) to generate lesson plans, presentations, and podcasts. Our system enhances the quality of generated materials through diverse input modalities, refined generation mechanisms, and interactive feedback with teachers. Specifically, we present the Plan10k dataset—a high-quality bilingual collection of lesson plans—and employ it to train and evaluate our framework. The pipeline consists of three main modules: a query rewriting module that handles multimodal teacher inputs (e.g., textual concepts, images, or textbook excerpts), a lesson plan generation module that produces structured content, and a chapter correction module that integrates retrieval-based tools to improve factual accuracy and contextual relevance. Furthermore, teachers can interact with intermediate results, allowing adaptive refinement throughout the generation process. Based on the generated lesson plans, the framework further produces corresponding visual presentations and podcasts, forming a comprehensive multimodal teaching assistant system. Extensive experiments and teacher evaluations demonstrate the superior performance and satisfaction of our approach. Full article

Graphs are used in school, many occupations, and daily life, yet many people struggle to interpret them accurately. To help identify sources of difficulty in graph comprehension, we propose the Pictorial–Semantic–Task Framework. In it, we argue that accurate interpretation of graphs requires integrating pictorial variables (e.g., slope direction, graph format, data points) with semantic variables (e.g., titles, labels, scales, variable types) to determine what the graph represents. Many errors arise because readers fail to coordinate these two sources of information, often basing interpretations solely on pictorial variables. The present theoretical synthesis presents the basic analysis underlying the Pictorial–Semantic–Task Framework and an integrative review of relevant findings from graph encoding, extrapolation, and comparison tasks. The findings show that people encode and recall pictorial information far more accurately than semantic information, and often base interpretations solely on visual patterns even when semantic features call for a different conclusion. Analyses of U.S. textbooks and mass media reveal potential sources of these biased interpretations: systematic imbalances in the types of semantic information provided in textbooks and media seem likely to contribute to biases, emphasizing visual over semantic cues. By describing how perceptual and conceptual processes interact during graph comprehension, we aim to advance theories of cognitive processing in the context of graph comprehension and to derive educational implications for helping children interpret graphs more accurately. Full article

This review summarizes the existing literature to investigate the role of excessive dynamic genu valgum (DGV) upon landing on subsequent movement performance in athletes. General systems theory and kinetic chain theory comprise the underlying theoretical frameworks, with an emphasis on regional interdependency in the context of lower-limb kinematics. Using a snowballing methodology, information was obtained from PubMed, CINAHL, Wiley Online Library, ProQuest, and Scopus databases, as well as through the utilization of Google Scholar and relevant biomechanics and movement analysis textbooks. Limitations include a paucity of research in the absence of injury and on DGV and subsequent performance post landing. Numerous factors, such as strength deficits of the predominant stabilizers of the knee in the frontal plane, fatigue, presence of dual tasks, and ingrained motor control, may influence medial knee excursion upon landing. Increased medial knee excursion during the transition from force attenuation to control is theorized to reduce the mechanical advantage of the quadriceps, impairing the efficiency of the stretch–shortening cycle for subsequent athletic movement performance. Mechanical and cognitive factors may influence knee biomechanics during landing and subsequent movement efficiency; however, the existing literature would benefit from further exploration of the differences in movement mechanics (e.g., acceleration) post landing in excessive DGV and the role of the trunk and subtalar joint on knee kinematics through the context of regional interdependency. This review is novel in investigating DGV from the perspective of movement performance rather than injury. Full article

In this paper we compare the rotation of a rigid body in the real three-dimensional Euclidean space E³ and its representation in the complex plane (Klein space), on one hand, with the transformation of polarization states of light (SOPs) by the phase-shifters figured in the complex plane and on the Poincaré sphere, on the other hand. Both the Klein space, in classical mechanics, and the Poincaré sphere, in polarization theory, are abstract spaces, whose construction is based on the classical stereographical projection between Riemann sphere and the simple complex plane C¹. They are classical abstract spaces, even if they have been largely used for representing quantum spinorial physical realities too. At the interface of classical/quantum physics persist some misaperceptions about what is intrinsically of quantum origin and nature, and what is imported from the classical domain. In this context we examine some misunderstandings that take place in the field of these spaces. I shall focus on the double angle relationship between the rotation of representative points of the SOPs on the Poincaré sphere with respect to the corresponding rotations of the azimuthal and ellipticity angles of the “form of the SOPs”, at a transformation of state given by a phase shifter. This is a classical result, that is transferred on the sphere from the complex plane, on the basis of the stereographic bijective connection between the points on the sphere and those in the complex plane. In any textbook of quantum mechanics “the double angle/half angle problem” is presented as a pure quantum spinorial one, avoiding its classical face and origin. A quantum spinorial approach, obviously, recovers the classical results, together with the specific spinorial ones, but with regards to the double angle/half angle issue it is superfluous. We shall also briefly examine the classical and quantum spinorial content of what we know today under the global name of Pauli spin matrices. Often in papers or textbooks of physics the results are presented in a mélange in which it is difficult to establish from which point on one needs to appeal to spinorial or quantum aspects. Full article

The most widespread lesson preparation resource used by mathematics teachers is the textbook. Initial teacher training programmes should therefore develop the skill of curricular noticing, i.e., the ability to critically analyse and make decisions concerning an activity sequence from a textbook. This mix-method study focused on the interpretations and decisions adopted by 85 Spanish pre-service primary school teachers (PTs) in relation to a three-dimensional (3D) geometry activity sequence from a textbook. The PTs were assigned two tasks: the first was identifying the limitations of the activity sequence for supporting students’ geometrical understanding regarding three aspects—attributes, geometrical processes, and modes of representation—and the second was completing the sequence. Most PTs interpreted a number of activity sequence limitations. In terms of their decision-making, the PTs prioritised certain characteristics over others, such as introducing further attributes rather than changing representation modes, or adding geometrical processes to their activity sequence designs. Moreover, the analysis allowed determining how PTs completed the activity sequence to address limitations, thereby revealing relationships between their interpretations and decisions. The study findings help teacher educators to design courses aimed at supporting the PTs’ ability to make more informed and effective teaching choices that enhance student learning. Full article

In contemporary education, learners face the challenge of navigating an overwhelming abundance of information. Traditional search methods, often limited to keyword matching, fail to capture the nuanced meaning and relationships within educational materials. Our multimodal approach combines Sentence Transformer for text and Inception V3 for images to generate vector embeddings for textbooks which are stored in an Elasticsearch database. Learners’ queries again are converted to vector embeddings which are matched through cosine similarity with stored embeddings, resulting in retrieval of relevant material which is ranked and then synthesized using large language model (LLM) APIs. The approach retrieves answers based on semantic search rather than keywords. The system also integrates GenAI capabilities separately, specifically leveraging LLM APIs, to generate context-aware answers to user-posed questions at varying levels of complexity, e.g., beginner, intermediate, and advanced. Through comprehensive evaluation, we demonstrate the system’s ability to retrieve coherent answers across multiple sources, offering significant advancements in cross-text and cross-modal retrieval tasks. This work also contributes to the international discourse on ethical GenAI integration in curricula and fosters a collaborative human–AI learning ecosystem. Full article

Background: Digitalisation is transforming medical education, but its integration into ultrasound training remains limited. This study evaluates the needs of students and physicians regarding digitally supported ultrasound education. Materials and Methods: A multi-year cross-sectional study (2017–2022) employed two standardised questionnaires. The first assessed the perceived relevance of ultrasound in medical education, the desirability of compulsory teaching, and the integration of digital media and case-based learning. The second explored user-centred requirements for e-learning formats, including functionality, multimedia design, usability, interactivity, and financing, as well as current use of digital devices and reference materials. Data were collected using dichotomous and 7-point Likert scales (1 = high need/strong agreement, 7 = low need/weak agreement). Results: A total of 3479 responses were analysed (2821 students; 658 physicians). Both groups showed strong support for integrating ultrasound into curricula (1.3 ± 0.7) and mandatory education (1.4 ± 0.9), with students expressing significantly greater support (p < 0.001). There was broad agreement on the integration and development of digital media (1.7 ± 1.0), as well as the use of case studies (1.4 ± 0.8), with no significant differences between groups (p > 0.05). Case-based learning as a stand-alone format was less favoured (3.4 ± 1.9). In the user-centred needs analysis, both groups rated features like search functions (1.4 ± 0.8), usability (1.5 ± 0.9), and learning objective checks (2.7 ± 1.6) as important. High-quality media (1.5 ± 0.9) and pathology explanations (1.6 ± 1.1) were also highly valued. Students primarily relied on digital platforms, while physicians used a more varied mix of digital platforms, guidelines, and textbooks. Conclusions: The study highlights the need for more extensive, digitally supported ultrasound training, with a focus on functionality and usability. Standardisation through structured certification processes should be considered for future implementation. Full article

The article discusses the challenges faced by primary and secondary school students in North Macedonia, focusing on the availability of textbooks for those receiving instruction in minority languages. Although some materials are available for download on the E-učebnici platform operated by the Ministry of Education and Science, this does not encompass all didactic resources required for instruction. Cataloging of the materials on the platform reveals that while electronic versions of many textbooks in Macedonian are freely accessible, students studying in Albanian (a co-official language) and minority languages such as Turkish, Bosnian, and Serbian have considerably fewer digital resources. The data indicate that disparities begin from the fifth grade and widen in higher grades, with Bosnian- and Serbian-speaking students particularly disadvantaged. In vocational education, Macedonian-speaking students have the broadest access to electronic materials, while Albanian and especially Turkish speakers have far fewer options, and no digital textbooks are available in Serbian. The analysis demonstrates that a semi-official hierarchy of languages persists within North Macedonia’s educational system, privileging Macedonian and, to a lesser extent, Albanian, while marginalizing other minority languages both institutionally and technologically. The article concludes by outlining the challenges and implications of implementing digital resources as a means to address linguistic inequality in education. Full article

Objectives: The main aim was to evaluate the origin and empirical support of the current diagnostic criteria for (hypo)manic and depressive episodes in BD focusing on their nosological (i.e., is it a real entity?) and diagnostic validity (i.e., how well do the criteria for the category portray the entity?). Methods: A narrative review of relevant textbooks/reports and articles published in peer-reviewed English-language journals (from the online databases PubMed and PsycInfo), covering the period 1900–2024 and using the terms “validity” OR “diagnosis” AND “manic-depressive”; “mania”; “hypomania”; “depression”; and “melancholia” was performed. Results: Mania appears to be a valid construct in nosological terms, although its validity in the diagnostic domain requires further research. There are scant and controversial empirical data on the nosological validity of separating hypomania from mania as different episodes. The current concept of bipolar depression combines different forms of episodes (melancholic and non-melancholic, with or without psychosis, recurrent or not) without conclusive evidence that all of them are necessarily part of the illness (i.e., limited nosological validity). Conclusions: The validity of the current definition of BD is limited and should be the focus of future research. A valid definition of BD would improve our ability to understand the pathophysiological basis of the illness and contribute to more tailored therapeutic approaches. Full article