technologie_educative_articles

Turkish adaptation of a new scale for measuring transactional distance between students and the learning technology

Thu, 02 Oct 2025 08:20:13 +0000

Author Names: Yandi A.

Database Source: Embase Daily Updates

Journal Title: PLOS ONE

Article Title: Turkish adaptation of a new scale for measuring transactional distance between students and the learning technology

Year: 2025

Issue: 9 September

Volume: 20

Abstract: Transactional distance is a key construct for understanding the quality of interactions in distance education. This study aimed to adapt the New Scale for Measuring Transactional Distance Between Students and Technology to Turkish culture. The adaptation process followed the 18-step guideline by the International Test Commission (ITC). The scale was applied to two study groups: Study Group 1 (n=46) for linguistic equivalence and preliminary analysis, and Study Group 2 (n=2402) for validation. Confirmatory factor analysis confirmed the four-factor structure with acceptable fit indices (CFI=0.964, TLI=0.947, RMSEA=0.079, SRMR=0.049). The reliability coefficients (Cronbach's alpha) ranged from 0.702 to 0.939 across dimensions. Discriminant validity was supported through HTMT2 values, all below 0.90. The results suggest that the adapted scale is a valid and reliable tool for measuring transactional distance in Turkish distance education contexts. Copyright © 2025 Alperen Yandi. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Technology-enhanced Quality Physical Education Impacting Moderate-to-Vigorous Physical Activity And Cardiorespiratory Fitness: 968...American College of Sports Medicine (ACSM) Annual Meeting, May 27-30, 2025, Atlanta, Georgia.

Thu, 02 Oct 2025 04:00:00 +0000

Medicine & Science in Sports & Exercise; 10/02/2025
(AN 187999751); ISSN: 01959131
CINAHL Complete

1356 Utilizing Machine Learning Technology to Predict Acute Events in Patients Living in Long-term Care Facilities: a Literature Review Analysis

Wed, 01 Oct 2025 08:22:47 +0000

Author Names: Park Y.J.,Kim H.,Song M.

Database Source: Embase Daily Updates

Journal Title: Journal of the American Pharmacists Association

Article Title: 1356 Utilizing Machine Learning Technology to Predict Acute Events in Patients Living in Long-term Care Facilities: a Literature Review Analysis

Year: 2025

Issue: 5

Volume: 65

Abstract: Objectives: Objectives: To analyze the effectiveness of artificial intelligence-based predictive analytics in identifying various acute events in long-term care facilities such new onset delirium and fall risk in older adults. Background(s): Adults living in long-term care facilites are predisposed to a number of health risks such as, but not limited to delirium and fall risks. Delirium is a sudden and serious change in mental function that can affect a person's behavior and ability to function, often characterized by alteration of attention, consciousness, and cognition, with a reduced ability to focus, sustain or shift attention. This disorder is very prevalent among older adults, especially in long-term care settings, and is associated with increased mortality rates and can even lead to severe complications if not addressed in a timely manner. Another health issue often faced by adults in long-term care facilities is the risk of experiencing a fall. There are various factors that contribute to this risk including the physical equipment, as well as patient-specific conditions like dementia, visual impairment, and overall reduced mobility. With falls come a risk of broken bones, concussions, and other injuries which in a population who are more frail can bring about further complications. These combined with the growing scope of artificial intelligence, can give AI the potential to transform the way various events can be predicted and treated through enabling earlier diagnosis, personalizing treatment plans, and improving patient monitoring, to improve the quality of life and care for these patients. Method(s): A literature review was conducted to analyze the types of and effectiveness of machine-learning in early identification of delirium and fall risks in older adults living in long-term care facilities. PubMed MEDLINE, Cochrane Library, IEEE Xplore, and Web of Science were searched to find relevant studies. Keywords like Medical Subject Heading (MesH) terms were tailored to each database and studies were eligible for inclusion if they studied a population of patients living in long-term care facilities and had an artificial intelligence-based intervention. Result(s): Data abstraction for the systematic literature review is currently in progress. Conclusions/Implications: While data abstraction is still in progress, preliminary research shows promise in the implementation of artificial intelligence (AI) in long-term care facilities for early identification of delirium, falls, and infections. Additionally, there also appears to be potential benefits of the use of AI in not only predicting acute events but also in addressing other problems faced by long-term care residents like loneliness and social isolation. Copyright © 2025

Building MHealth technology for Health Promotion in Reproductive Planning: innovations in primary care

Wed, 01 Oct 2025 08:22:47 +0000

Author Names: de Lima E.R.,Feliciano A.B.,Galon T.,de Oliveira C.A.N.,Frizzo H.C.F.

Database Source: Embase Daily Updates

Journal Title: Ciencia e Saude Coletiva

Article Title: Building MHealth technology for Health Promotion in Reproductive Planning: innovations in primary care,Construcao de tecnologia MHealth para Promocao da Saude em Planejamento Reprodutivo: inovacoes na atencao primaria,Construccion de tecnologia MHealth para la Promocion de la Salud en la Planificacion Reproductiva: innovaciones en atencion primaria

Year: 2025

Issue: 8

Volume: 30

Abstract: Reproductive Planning is a recognized basic human right and is essential to guaranteeing the quality of health providers' work processes in Primary Health Care (PHC). This study aimed to build a prototype of a mobile application on reproductive planning to aid the ongoing education of nurses in PHC. This methodological study is based on four stages: modeling, navigation design, abstract interface design, and implementation, and was built based on the thematic categorization of article contents stemming from an integrative review, totaling 24 moblets. The initial screen is presented to access educational technology, including the key that enters the application, the contents, the other interfaces, and the presentation of the theme involved. Relevant content was emphasized for a person-cen-tered approach, with quick and easy access to content available in just one click, involving key aspects: promoting welcoming, qualified listening, creating bonds and trust, and contraceptive counseling. Its applicability with simple language, easy access, and usability, together with a clear content based on up-to-date evidence, will offer greater quality and efficiency of care. Copyright © 2025, Associacao Brasileira de Pos - Graduacao em Saude Coletiva. All rights reserved.

Efficacy of a smart glass-enhanced training programme for core doctor-patient communication skills among radiology residents in China

Wed, 01 Oct 2025 08:22:47 +0000

Author Names: Xiao Y.,Lian G.,Zhang J.,Chen Q.,Wang H.,Huang L.,Yang H.,Zhu C.,Mei W.,Zhuang C.,Zhong C.,Huang R.

Database Source: Embase Daily Updates

Journal Title: European Radiology Experimental

Article Title: Efficacy of a smart glass-enhanced training programme for core doctor-patient communication skills among radiology residents in China

Year: 2025

Issue: 1

Volume: 9

Abstract: Background: Effective doctor-patient communication (DPC) skills are critical competencies in residency training. This study evaluated the efficacy of a smart glass (SG)-based communication skills training curriculum for radiology residents in China. Material(s) and Method(s): This quasi-experimental study with a one-group pretest-posttest design involved 18 radiology residents in an 8-week SG-based DPC simulation training. Supervisors used the SEGUE scale, while residents and four standardised patients (SPs) trained by the Guangdong Institute of Simulation Medicine self-assessed satisfaction with a Likert scale. Analysis compared pre- and post-training scores (before, immediately after, and 6 months post-programme). Post-training SG experiences were assessed via surveys. Result(s): Significant improvements were observed in SEGUE scale scores immediately and 6 months post-programme compared with pre-programme scores (17.06 +/- 3.67 and 17.72 +/- 3.12 versus 10.94 +/- 2.88, respectively, p < 0.001). Similarly, Likert scores for SPs and residents showed significant increases both immediately and 6 months post-programme compared with initial scores (3.50 +/- 0.51 and 3.67 +/- 0.68 versus 2.39 +/- 0.61, p < 0.001 for both, and 3.28 +/- 0.46 and 3.55 +/- 0.78 versus 2.66 +/- 0.84, p = 0.037 and 0.008, respectively). Post-training, the Likert consistency between SPs and residents was 0.73 (p = 0.005). Of 18 participants, 16 (89%) reported that SG provided useful feedback, and 16 (89%) recognised the value of SG in developing DPC skills. Conclusion(s): The SG-based simulation training programme significantly enhanced and sustained DPC skills among radiology residents. Relevance statement: Smart glasses provide an innovative tool for recording standardised patient encounters, offering a perspective for analysing and evaluating residents' interpersonal communication skills and nonverbal behaviours. Key Points: Smart glasses enhance doctor-patient communication skills in radiology residents. Simulation training with smart glasses showed improvement in skills. Smart glasses offer a perspective for standardised patient encounters. They facilitate better analysis of residents' interpersonal and nonverbal communication. Copyright © The Author(s) 2025.

1259 Current Use of Artificial Intelligence and Machine Learning Technologies in Antimicrobial Stewardship Programs: Scoping Review

Wed, 01 Oct 2025 08:22:47 +0000

Author Names: Dinh T.,Kang A.,Minejima E.,Portillo I.,Tran P.

Database Source: Embase Daily Updates

Journal Title: Journal of the American Pharmacists Association

Article Title: 1259 Current Use of Artificial Intelligence and Machine Learning Technologies in Antimicrobial Stewardship Programs: Scoping Review

Year: 2025

Issue: 5

Volume: 65

Abstract: Objectives: This study aims to investigate current state of research on the utilization of AI and machine learning technologies in ASP, and how these technologies impact the workload and intervention strategies of ASP pharmacists. Antimicrobial stewardship program (ASP) commonly utilizes a prospective audit with feedback (PAF). This PAF activity can be labor intensive for antimicrobial stewardship teams. Therefore, improving efficiency in PAF activities is crucial. While there have been several publications that investigated the use of artificial intelligence (AI), primarily through statistical and machine learning approaches, to identify interventions that may lead to actionable plans, there has yet to be a comprehensive review of the literature on this topic. Method(s): The search was conducted on July 10, 2024, using databases including Ovid Medline, Embase, IPA, Web of Science, and CINAHL. The search strategy included keywords such as "antimicrobial stewardship," "antibiotic stewardship," "machine learning," and "artificial intelligence," without language restrictions. The search covered all articles from the start of each database until July 2024. All discovered articles were managed through EndNote 21 and Zotero. Two reviewers independently evaluated articles for inclusion based on criteria through Rayyan software. If necessary, a third final reviewer made a decision if there are any disagreements between the first two reviewers. The data extraction will be performed through REDCap after going through a pilot test of 3 articles. We will extract data using a predeveloped data extraction form. The data extraction will be limited to the predefined outcomes of interest. Extracted data will undergo a verification process by a second team member, and discrepancies will be resolved by a third team member. The quality of the articles will be assessed using the Newcastle-Ottawa Scale (NOS) to help gauge quality and bias. Result(s): Our search has populated over 105 articles. Out of those 105 articles, 10 were included at the end of extraction. Conclusions/Implications: This scoping review aims to provide a comprehensive overview of the current research on the utilization of AI and machine learning technologies in ASPs. By synthesizing available evidence, this review will identify gaps in the literature and assess the potential for AI-driven models to enhance the efficiency of ASPs and reduce the workload of infectious disease pharmacists. The findings of this review are expected to inform future research directions and the feasibility of integrating AI into clinical workflows to optimize antimicrobial stewardship efforts. Copyright © 2025

Patterns, advances, and gaps in using ChatGPT and similar technologies in nursing education: A PAGER scoping review.

Wed, 01 Oct 2025 04:00:00 +0000

Nurse Education Today; 10/01/2025
Generative AI (GenAI) can transform nursing education and modernise content delivery. However, the rapid integration of these tools has raised concerns about academic integrity and teaching quality. Previous reviews have either looked broadly at artificial intelligence or focused narrowly on single tools like ChatGPT. This scoping review uses a structured framework to identify patterns, advances, gaps, evidence, and recommendations for implementing GenAI in nursing education. This scoping review followed the JBI methodology and PRISMA-ScR guidelines. We searched PubMed, CINAHL, SCOPUS, ERIC, and grey literature (October to November 2024). Data synthesis utilised the PAGER framework as a mapping tool to organise and describe patterns, advances, gaps, evidence for practice, and recommendations. Analysis of 107 studies revealed GenAI implementation across four key domains: assessment and evaluation, clinical simulation, educational content development, and faculty/student support. Three distinct implementation patterns emerged: restrictive, integrative, and hybrid approaches, with hybrid models demonstrating superior adoption outcomes. Technical advances showed significant improvement from GPT-3.5 (75.3 % accuracy) to GPT-4 (88.67 % accuracy) in NCLEX-style assessments, with enhanced capabilities in multilingual assessment, clinical scenario generation, and adaptive content creation. Major gaps included limited methodological rigour (29.0 % of empirical studies), inconsistent quality control, verification challenges, equity concerns, and inadequate faculty training. Geographic distribution showed North American (42.1 %) and Asian (29.9 %) dominance, with ChatGPT representing 83.2 % of tool implementations. Key recommendations include developing institutional policies, establishing quality verification protocols, enhancing faculty training programs, and addressing digital equity concerns to optimise GenAI integration in nursing education. GenAI has transformative potential in nursing education. To realise its full potential and ensure responsible use, research should focus on developing standardised governance frameworks, empirically validating outcomes, developing faculty in AI literacy, and improving technical infrastructure for low-income contexts. Such efforts should involve international collaboration, highlighting the importance of the audience's role in the global healthcare community. • GenAI is used in nursing assessment, simulation, and content development. • GPT-4 scored 88.7 % on NCLEX-style questions, outperforming GPT-3.5. • Only 29 % of studies used empirical designs to assess GenAI outcomes. • GenAI improved simulation realism and personalised learning feedback. • Safe GenAI use requires faculty training and a clear institutional policy.
(AN 187140066); ISSN: 02606917
CINAHL Complete

Leveraging Quick Response Codes to Promote Learner-Centered Simulation.

Wed, 01 Oct 2025 04:00:00 +0000

Teaching & Learning in Nursing; 10/01/2025
• Simulation provides support for students to achieve behavioral competencies. • Quick response codes can provide data to inform a learner-centered approach. • Educators can use this technology to quickly improve teaching in simulation.
(AN 187941148); ISSN: 15573087
CINAHL Complete

Development of a board game to teaching electrocardiograms in undergraduate nursing.

Wed, 01 Oct 2025 04:00:00 +0000

Teaching & Learning in Nursing; 10/01/2025
• The educational technology such can help way apprenticeship. • The board game validated assists teaching electrocardiogram. • Was developed and valid with experts and student and is easy to apply by teachers. The teaching of electrocardiograms is still deficient, the knowledge interpreting is low, due to the prevalence of traditional teaching. It is necessary to initial training incorporate teaching strategies that are easy application. To develop an educational board game for teaching electrocardiograms in undergraduate nursing courses. design methodological study. Carried out in the years 2021 to 2023, in the following stages: 1) Construction of the game; 2) Validation of appearance and content with experts; 3) Semantic validation with nursing students. The "Uncomplicating the ECG" game consists of a board with cards containing questions/announcements and challenges about the electrocardiogram and its clinical use. The board game was validated by 11 experts, with a total agreement level of over 80% for its content and appearance, over 90% in the semantic analysis of the target audience of 11 students, and a statistical α-Cronbach's test above 0.70. The board game developed is valid as an alternative for nursing faculty to teach electrocardiograms, and students actively and playfully and interaction acquire knowledge.
(AN 187941125); ISSN: 15573087
CINAHL Complete

Utilization of metaverse environment for education among nursing students based on personality traits and digital literacy.

Wed, 01 Oct 2025 04:00:00 +0000

Clinical Simulation in Nursing; 10/01/2025
• Exploring Metaverse's impact on nursing education, focusing on traits and literacy. • Traditional methods may not meet diverse needs; Metaverse offers unique engagement. • Introverted students report higher satisfaction, suggesting suitability for fewer interactions. • Study's limited scope may restrict generalizability of findings to one college and a subject. • Metaverse education transforms nursing by accommodating diverse learning styles. The metaverse, a virtual reality space that enables real-time interaction, is increasingly being integrated into education, as traditional classrooms often fail to meet the diverse student needs. This study examined nursing students' satisfaction, self-efficacy, and learning experiences within a metaverse-based collaborative learning environment, focusing on the influence of personality traits and digital literacy. A quasi-experimental, one-group post-test design was employed with 40 nursing students. Additionally, 15 students participated in focus group interviews (FGI). The relationships between personality traits, digital literacy, and metaverse satisfaction were analyzed using t-tests, chi-square tests, and Pearson's correlation coefficients. Interview data were examined using content analysis. Digital literacy was positively correlated with self-efficacy and course satisfaction. Introverted students reported reduced presentation anxiety, whereas extroverted students exhibited lower platform satisfaction. The interviews identified usability issues and emphasized the need for structured guidance for students with high neuroticism. While, the metaverse can support diverse learning needs, careful integration is essential to address usability concerns and to provide structured guidance tailored for certain students.
(AN 188057121); ISSN: 18761399
CINAHL Complete

Optimizing online nursing education leveraging the GUARD system and ONE Guide for enhanced communication and best practices.

Wed, 01 Oct 2025 04:00:00 +0000

Nursing; 10/01/2025
(AN 188124155); ISSN: 03604039
CINAHL Complete

ChatGPT in Education: An Effect in Search of a Cause.

Wed, 01 Oct 2025 04:00:00 +0000

Journal of Computer Assisted Learning; 10/01/2025
Background: As researchers rush to investigate the potential of AI tools like ChatGPT to enhance learning, well‐documented pitfalls threaten the validity of this emerging research. Issues of media comparison research, where the confounding of instructional methods and technological affordances is unrecognised, may render effects uninterpretable. Objectives: Using a recent meta‐analysis by Deng et al. (Computers & Education, 227, 105224) as an example, we revisit key insights from the media/methods debate to highlight recurring conceptual challenges in ChatGPT efficacy studies. Methods: This conceptual article contrasts nascent ChatGPT research with the more established literature on Intelligent Tutoring Systems to identify three non‐negotiable considerations for interpretable effects: (1) descriptions of the precise nature of the experimental treatment and (2) the activities of the control group, as well as (3) outcome measures as valid indicators of learning. To provide some initial evidence, we audited a subset of primary experiments included in Deng et al.'s meta‐analysis, demonstrating that only a small minority of studies satisfied all three non‐negotiable considerations. Results and Conclusions: Loosely defined treatments, mismatched or opaque controls, and outcome measures with unclear links to durable learning obscure causal claims of this emerging literature. Observed gains cannot, at this time, be confidently attributed to ChatGPT, and meta‐analytics effect sizes may over‐ or understate its benefits. Progress, we argue, will require rigorous designs, transparent reporting, and a critical stance toward "fast science."
(AN 188234203); ISSN: 02664909
CINAHL Complete

Exploring the Effects of the CER Model‐Based GenAI Learning System to Cultivate Elementary School Students' Computational Thinking Core Skills in Science Courses.

Wed, 01 Oct 2025 04:00:00 +0000

Journal of Computer Assisted Learning; 10/01/2025
Background: Computational thinking (CT) is a fundamental ability required of individuals in the 21st‐century digital world. Past studies show that generative artificial intelligence (GenAI) can enhance students' CT skills. However, GenAI may produce inaccurate output, and students who rely too much on AI may learn little and be unable to think independently. Besides, most research on CT mainly focused on Scratch or programming classes, but incorporating it into the K‐12 science curriculum is better for students' deep learning and CT core skills development. Objectives: This study proposed a causal explanation and reflection (CER) model‐based GenAI learning system in science courses to cultivate students' CT core skills. Sample: One hundred and eighteen elementary school students in three different classes participated in this study. Methods: A quasi‐experiment was conducted in Fujian, China. Students in the experimental group learned with the CER model‐based GenAI learning system; students learned with the CER model‐based learning system in control group 1; students in control group 2 used the causal‐explanation‐based GenAI learning system. Students' learning achievement and CT core skills were examined. Results: The results showed that the CER model‐based GenAI learning system significantly improved students' science learning and CT core skills. Interview results further showed some students complained that GenAI only provided answers without encouraging them to comprehend the material. Conclusions: CT should not exist only in computer courses. Instead, it is an approach to problem‐solving that applies to all disciplines. Also, over‐reliance on GenAI may hinder learning ability. The effectiveness of GenAI‐based learning depends on its judicious use.
(AN 188234208); ISSN: 02664909
CINAHL Complete

Learning Achievement in Virtual Reality/Animation‐Based Business Simulation Games: An Integrated View of Goal Orientations, Model‐Reality Fit, Learning Anxiety and ARCS Motivation.

Wed, 01 Oct 2025 04:00:00 +0000

Journal of Computer Assisted Learning; 10/01/2025
Background: Goal orientations (GO) are influential achievement goals in predicting achievement motivation and effectiveness. However, few studies have paid specific attention to investigating the effects of GO on learning achievement in the area of business management education. Objectives: This study developed a business simulation game system (BSGS) for supporting learning to investigate how GO affects students' learning achievement in the context of business management education. Methods: A total of 209 college/undergraduate students participated in this study, and they were divided into the experiment group (EG) and the control group (CG). A quasi‐experiment was conducted to understand how students' achievement goals and the use of BSGS modules can enhance their motivation and reduce their learning anxiety, thus affecting learning achievement. Results and Conclusions: The results showed that most students adopted a mastery/learning‐GO to complete the learning tasks in their learning processes. A high level of model‐reality fit significantly reduced students' learning anxiety. However, learning anxiety did not affect students' learning achievements. Implications: The results of this study indicate that model‐reality fit plays an important role in increasing learning expectations and achievements and decreasing learning anxiety, which could benefit students' learning achievement in BSGS‐supported educational contexts.
(AN 188234227); ISSN: 02664909
CINAHL Complete

Leveraging Machine Learning Approach to Identify the Predictors of Informal Digital Learning of English Behaviours Among EFL Learners.

Wed, 01 Oct 2025 04:00:00 +0000

Journal of Computer Assisted Learning; 10/01/2025
Background Study: With the rapid transition to remote learning necessitated by the closure of traditional educational infrastructures globally, the arena of informal digital learning of English (IDLE) has received much attention, particularly among English as a Foreign Language (EFL) learners in China. Objective: This study explores how demographic variables (gender, age, grade, major, and background) along with confidence, desire, online self‐efficacy, attitudinal belief, and intention to learn English predict IDLE behaviours among EFL learners in IDLE contexts. Methods: Utilising a comprehensive dataset, the research incorporates machine learning algorithms (e.g., Random Forest, Support Vector Machine, Logistic Regression, Decision Tree, Gradient Boosting Decision Tree and Adaptive Boosting (AdaBoost)) to analyse psychological, behavioural and demographic predictors of IDLE behaviours. Participants included 2, 055 EFL learners in China. Results: The study finds that EFL learners' confidence, desire, online self‐efficacy, attitudinal belief, intention to learn English and IDLE behaviours display a moderate level. Moreover, confidence and desire act as the strongest predictors of IDLE behaviours, whereas demographic variables (gender, age, grade, major and background) predict the minimum of IDLE behaviours. Conclusion: By understanding these predictors, educational strategies can be better tailored to enhance digital education outcomes.
(AN 188234209); ISSN: 02664909
CINAHL Complete

Revolutionising Higher Education: A Big Data‐Driven Approach to Intelligent Supervision Platforms in Universities.

Wed, 01 Oct 2025 04:00:00 +0000

Journal of Computer Assisted Learning; 10/01/2025
Background: The creation of Intelligent Supervision Platforms in universities leverages Big Data for robust monitoring and decision‐making, which significantly enhances overall efficiency and adaptability in educational environments. Objectives: This research focuses on evaluating how Big Data‐driven Intelligent Supervision Platforms in universities influence core institutional outcomes, namely, perceived academic performance, student retention, faculty productivity, and data‐informed decision‐making. The study prioritises these key variables to demonstrate the strategic role of Intelligent Supervision Platforms in enhancing higher education performance. Methods: Data were gathered from 420 students and 118 teachers using a questionnaire method, and the quantitative data were analysed with Statistical Package for the Social Sciences (SPSS) software. The novelty of this study lies in its focus on the development of intelligent supervision platforms tailored specifically for the unique needs and dynamics of university settings. Results: The findings show that the implementation of intelligent supervision platforms, driven by Big Data analytics, positively affects students' perceived academic performance. Conclusions: The integration of Big Data analytics into intelligent supervision platforms can significantly enhance decision‐making processes and support personalised learning experiences; such platforms improve faculty and staff productivity, streamline administrative operations, and optimise resource allocation within universities, ultimately contributing to a more efficient and effective educational environment.
(AN 188234196); ISSN: 02664909
CINAHL Complete

Seventh‐Grade Students' Views Regarding Enriched Algebra Instruction (EAI) Supported by Technology and Manipulatives.

Wed, 01 Oct 2025 04:00:00 +0000

Journal of Computer Assisted Learning; 10/01/2025
Background: Previous research has shown that students often struggle to understand algebraic expressions and solve equations, and that traditional instructional approaches may not be sufficient to address these challenges. While the use of technology and physical manipulatives independently has been shown to support students' conceptual understanding in algebra, limited research has examined their combined use—particularly the integration of dynamic mathematics software and manipulatives—within the context of algebra instruction. Objectives: This study aims to explore seventh‐grade students' perceptions of an enriched algebra instruction (EAI) approach that integrates dynamic mathematics software and physical manipulatives to support and enhance their learning experiences. Methods: A qualitative case study was conducted with 30 Turkish seventh‐grade students (aged 12–13). The EAI approach integrated technological tools, concrete materials, collaborative group work, and classroom discussions. Data were collected through a survey comprising 22 items rated on a 5‐point Likert‐type scale and four open‐ended questions, as well as through classroom observations. Quantitative data were analysed using descriptive statistics, while qualitative data were subjected to thematic content analysis. Results and Conclusion: Most students reported that the use of EAI, which integrates dynamic software and manipulatives, enhanced their active engagement in classroom activities, enabled them to conduct multiple experiments and observations, and facilitated visual interaction with the content. They also indicated that EAI helped them explore relationships within algebraic expressions, which they perceived as contributing to the development of their algebraic thinking and conceptual understanding.
(AN 188234199); ISSN: 02664909
CINAHL Complete

The Effects of Gamification on Students' Flow Experience.

Wed, 01 Oct 2025 04:00:00 +0000

Journal of Computer Assisted Learning; 10/01/2025
Background: Gamification has been used in recent years to enhance the student experience in educational environments and to help students achieve an optimal experience. However, there is limited empirical evidence of the effects of gamification on specific psychological experiences, such as the students' flow experience, which is a highly motivating state associated with the learning process. Objectives: To address this gap, we examined the impact of gamification on students' flow experience within a learning management system. Methods: We conducted a controlled between‐subjects experiment (N = 65) in which participants in the experimental group interacted with a gamified version of the system, which incorporated a typical gamification design consisting of a collection of various game elements that constituted a form of meta‐game interaction around the learning activity (as opposed to, for example, serious games or game‐based learning). In contrast, the participants in the control group used the same system with the same educational tasks but without gamification. We used descriptive and inferential statistical methods (i.e., Mann–Whitney U test) to compare the students' flow experience between the groups. Results and Conclusions: The results reveal that the influence of gamification on students' flow experience was not statistically significant. These findings suggest that current gamification designs may not effectively facilitate flow in educational contexts, highlighting the need for further research and development to align gamification with desired educational outcomes.
(AN 188234218); ISSN: 02664909
CINAHL Complete

Comparison of AI‐Generated and Instructor Feedback: No Significant Difference in Perceived Feedback Quality and Neither on Performance.

Wed, 01 Oct 2025 04:00:00 +0000

Journal of Computer Assisted Learning; 10/01/2025
Background: Feedback is an essential part of the educational process as it enriches students' learning experiences, provides information about their current performance, shows them what is lacking in achieving goals, and provides guidance on the strategies needed to achieve those goals. Teachers, especially in crowded classrooms, often have difficulty allocating enough time to provide feedback. ChatGPT has the potential to deliver feedback more efficiently and effectively. Objective: This study aims to investigate the effectiveness of ChatGPT‐generated feedback in students' project proposal development process. Therefore, ChatGPT‐generated and instructor's feedback are compared in terms of perceived feedback quality and performance of students. Method: In the study, a post‐test control group experimental design was used. A total of 48 students enrolled in a blended course at a state university participated in the study for 6 weeks. The study was conducted using a randomised post‐test‐only control group experimental design. Students were asked to prepare a project proposal and feedback was given on each task. While the control group received instructor feedback, the experimental group received ChatGPT feedback. Data were collected via the Formative Feedback Perceptions Scale, and the students' project proposals were graded based on the rubric to evaluate their performance. Results and Conclusion: According to the Mann–Whitney U test analysis, there was no statistically significant difference between the experimental and the control group regarding both students' perceived feedback quality and performance. In conclusion, it can be argued that when guided by the appropriate prompts and asked to examine assignments of similar complexity to those in this study, ChatGPT can provide feedback of similar quality and equivalence to the feedback provided by instructors. In this way, it seems possible to improve students' learning as much as an instructor with individualised feedback by ChatGPT. Finally, it should be noted that these findings are within the limitations of the specific context of project proposal development, reliance on self‐reported data, and the experimental nature of the study; it is recommended to evaluate the effectiveness of AI‐generated feedback in different contexts.
(AN 188234229); ISSN: 02664909
CINAHL Complete

Evaluating the Efficacy of an Intelligent Tutoring System That Integrates Affective Supports Into Math Learning.

Wed, 01 Oct 2025 04:00:00 +0000

Journal of Computer Assisted Learning; 10/01/2025
Background: Computer‐assisted educational technologies that integrate affective supports into math practices could be particularly beneficial for addressing troubling declines in middle grade students' math achievement, affect, and motivation. MathSpring is a web‐based intelligent tutor that offers personalised content, remedial tutoring, and affective support for students and diagnostic reports on students' progress and effort for teachers. Objectives: This preregistered randomised control trial experiment sought to experimentally test the efficacy of the MathSpring platform in improving students' math achievement and dispositions towards math. Methods: The final sample included 53 teachers and their 2003 10–12‐year‐old students from one U.S. state. Teachers were randomly assigned to either use MathSpring with their students (treatment condition) or continue business‐as‐usual math instruction (control condition) for one school year. Before and after the intervention, students' math achievement was measured with standardised math assessments and their dispositions towards math were measured with standardised surveys. Teachers completed logs, surveys, and interviews about their implementation. Results and Conclusions: The results indicated that students in the treatment group did not show evidence of improved achievement, affect, or dispositions towards math compared with students who received business‐as‐usual math instruction. Still, exploratory analyses indicated that students with high usage demonstrated greater achievement than those in the business‐as‐usual group. Though no overall effects of this intervention were detected, educational technology interventions with affective supports still hold potential for improving students' academic and dispositional outcomes.
(AN 188234204); ISSN: 02664909
CINAHL Complete

Artificial Intelligence (AI)-driven dental education: Exploring the role of chatbots in a clinical learning environment.

Wed, 01 Oct 2025 04:00:00 +0000

Journal of Prosthetic Dentistry; 10/01/2025
Despite their widespread use in various educational contexts, the integration of chatbots into dental clinical education has not been thoroughly investigated. The noted discrepancy signifies a lack of understanding of how chatbots could enhance the personalized and interactive learning experiences of predoctoral dental students. The purpose of this study was to evaluate the awareness and perceptions of artificial intelligence (AI) technology, interaction experiences, and concerns about a custom-developed chatbot (CB) intervention in the clinical education of predoctoral dental students at the University of Illinois Chicago, College of Dentistry (UIC-COD) compared with the traditional Blackboard (BB) online platform. Eligible participants (n=86) providing verbal consent were allocated via the random block method into BB (n=43) and CB (n=43) groups and asked to engage with their designated platforms for 10 to 15 minutes by focusing on clinical inquiries in a predoctoral implant clinic and supported by a list of 35 typical questions. After the interaction, participants responded on a 5-point Likert scale to a 19-item survey probing AI awareness, platform engagement, and technological concerns. Survey data were anonymized and analyzed using descriptive, inferential statistics and nonparametric Mann-Whitney U tests to compare interventions. The Bonferroni correction for multiple comparisons was performed (α=.0045). Neither the BB or CB group showed any difference in their awareness and perception of AI technology. The CB group demonstrated improved timeliness (P <.001), more interaction (P <.001), reduced faculty workload (P =.001), enhanced receptiveness (P =.002), and less anxiety (P <.001) and was more satisfied (P <.001) when compared with the BB group. However, concerns regarding the potential for incorrect information (P =.003) were more pronounced in the CB group. The integration of chatbot technology into dental clinical education significantly enhanced learning and student engagement, highlighting the potential for future technological enrichment of the educational landscape.
(AN 188237257); ISSN: 00223913
CINAHL Complete

Pilot Study of Arts-Based Learning for Oral Cancer Screening: Educational Outcomes

Sat, 27 Sep 2025 08:19:36 +0000

Author Names: Baabdullah R.,Alpert E.,Dor B.B.,Jiang T.

Database Source: Embase Daily Updates

Journal Title: Journal of dental education

Article Title: Pilot Study of Arts-Based Learning for Oral Cancer Screening: Educational Outcomes

Year: 2025

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Comment on "VAULT-OCT: Vault Accuracy Using Deep Learning Technology - An AI Model for Predicting Implantable Collamer Lens Postoperative Vault with AS-OCT"

Sat, 27 Sep 2025 08:19:36 +0000

Author Names: Tripathi M.,Markan A.

Database Source: Embase Daily Updates

Journal Title: Journal of cataract and refractive surgery

Article Title: Comment on "VAULT-OCT: Vault Accuracy Using Deep Learning Technology - An AI Model for Predicting Implantable Collamer Lens Postoperative Vault with AS-OCT"

Year: 2025

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Visuospatial ability and neuroanatomy learning in health profession education - A scoping review

Sat, 27 Sep 2025 08:19:36 +0000

Author Names: Anniesmitha K.,Mathias E.G.,Bandekar N.N.,Mohandas Rao K.G.,Ashwini Aithal P.,George B.M.

Database Source: Embase Weekly Updates

Journal Title: Translational Research in Anatomy

Article Title: Visuospatial ability and neuroanatomy learning in health profession education - A scoping review

Year: 2025

Issue:

Volume: 41

Abstract: Background: Neuroanatomy requires learners to interpret and mentally manipulate complex three-dimensional (3D) structures, making visuospatial ability (VSA) a critical factor for success. In recent years, educational technologies have emerged as promising tools to support spatial learning. However, the extent to which these technologies can enhance or compensate for learners' spatial skills remains unclear. Objective(s): This scoping review aimed to explore how various educational technologies impact the development or support of visuospatial ability in neuroanatomy education and to identify the assessment tools used to measure spatial ability across different studies. Method(s): A systematic search was conducted across PubMed, Scopus, CINAHL, Cochrane library, and Embase databases to identify studies that investigated the relationship between educational technology, spatial ability, and neuroanatomy learning. Included studies were analyzed for participant demographics, technology used, spatial ability assessment tools, and reported effects on VSA and learning outcomes. Result(s): Ten studies met the inclusion criteria, employing diverse technologies such as Virtual Reality (VR), Augmented Reality (AR), Mixed Reality (MR), interactive 3D modules, and volumetric imaging tools. Most studies used standardized psychometric tools like the Mental Rotations Test (MRT), Purdue Spatial Visualization Test (PSVT: R), or Santa Barbara Solids Test (SBST) to measure VSA. Evidence suggests that immersive technologies, particularly VR and MR, offer significant support to students with initially low spatial ability, narrowing the performance gap and, in some cases, enhancing spatial skills through repeated exposure and interactive visualization. While not all studies assessed VSA pre- and post-intervention, several studies reported improved spatial task performance and user engagement linked to technology use. Studies using 2D or non-immersive platforms showed limited benefit for low-VSA learners. Conclusion(s): Emerging educational technologies, especially 3D, VR, and MR tools, have shown potential not only to support but also to enhance visuospatial ability in the context of neuroanatomy education. Integrating these tools strategically could improve spatial reasoning and reduce disparities among learners with varying cognitive profiles. Future research should focus on longitudinal evaluations, standardized spatial assessments, and adaptive technologies that respond to learners' spatial needs. Copyright © 2025 The Authors

Enhanced Detection, Using Deep Learning Technology, of Medial Meniscal Posterior Horn Ramp Lesions in Patients with ACL Injury.

Wed, 17 Sep 2025 04:00:00 +0000

Journal of Bone & Joint Surgery, American Volume; 09/17/2025
(AN 188018160); ISSN: 00219355
CINAHL Complete

Serious play: evaluating the balance of knowledge and leisure content in environmental games.

Mon, 15 Sep 2025 04:00:00 +0000

Behaviour & Information Technology; 09/15/2025
In the context of increasing environmental degradation and climate change, promoting environmental awareness through innovative communication approaches is critical. This study examines the role of serious games in enhancing environmental information dissemination and in promoting continued engagement. Through two studies, the research investigates how different game content – knowledge-based versus leisure-focused – can impact user experience, environmental awareness, and continued game use. Study 1 explores the mediating role of customer experience between the interaction with each type of content and game effectiveness, while Study 2 employs an experimental approach to isolate game type effects and assess the role of negative emotions. Findings reveal that the balance between knowledge and leisure-content can be suitable vis-à-vis continued use of the game as long as both informativeness and playfulness are provided. However, when the aim is to promote environmental awareness, an isolated game focused on knowledge-content proves more effective, especially if it provides valuable information and evokes a sense of guilt in the user.
(AN 187842761); ISSN: 0144929X
CINAHL Complete

Application of head-mounted display-based augmented and mixed reality in nursing education: a scoping review.

Tue, 02 Sep 2025 04:00:00 +0000

BMC Nursing; 09/02/2025
Background: With Generation Z becoming the primary group of nursing learners and the increasing shortage of nursing education resources, augmented reality and mixed reality based on head-mounted displays are being used more and more in nursing education. However, the current application landscape and the proper usage of these concepts remain unclear. Therefore, this study aims to conduct a scoping review to explore the current applications of head-mounted display-based augmented reality and mixed reality in nursing education and to clarify the definitions and usage of the concepts of augmented reality and mixed reality, ultimately providing directions for future applications and research. Methods: Based on the five-stage framework and PRISMA-ScR guidelines, a comprehensive collection and summarization of evidence regarding the application of head-mounted display-based augmented reality and mixed reality in nursing education were conducted. The databases retrieved include CNKI, Wanfang Database, VIP, CBM, PubMed, Cochrane Library, Embase, CINAHL, Web of Science, Scopus, IEEE Xplore, ACM Digital Library, and Ei. The languages of the included literature are Chinese and English. The retrieval was up to October 2024. Results: A total of 44 studies were included in this review, covering three types of head-mounted displays: immersive head-mounted displays, smart glasses, and smartphone-based head-mounted displays. The main application areas were skills training and knowledge acquisition. Most of the studies were feasibility studies, though they also included some efficacy studies and research on personal experiences. In addition, these studies often employed vague or inconsistent definitions of augmented reality and mixed reality. Conclusions: Despite various explorations in the application of head-mounted display-based augmented reality and mixed reality in nursing education, there is still room for improvement in the relevant theory and utilization of this technology. In the future, interventions should use the three dimensions (observation of reality, real - virtual interaction, and fidelity of virtuality) described in detail, rather than simply employing the concepts of augmented reality or mixed reality. Efforts should be concentrated on developing and implementing head-mounted displays combined with other technologies that boast enhanced performance and cost - effectiveness, and further validating their effectiveness.
(AN 187699241); ISSN: 14726955
CINAHL Complete

From bedside to learning bench: Educational technology perspectives on ChatGPT-supported triage.