Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Article A Metaverse-Based Fully Immersive Training for Temporomandibular Joint: A Pilot Study(Wiley, 2026) Ozcelik, Erol; Ekici, Saliha Zerdali; Basmaci, Fulya; Cagiltay, Nergiz Ercil; Kilicarslan, Mehmet AliObjective Understanding the temporomandibular joint (TMJ) can be challenging with conventional methods, as its complex anatomy, comprising the articular disc, mandibular condyle, and temporal bone, requires detailed visualisation. Traditional approaches like textbooks and static images often fall short, whereas modern tools such as 3D modelling and virtual reality (VR) offer more effective alternatives. Metaverse technology further enhances this by creating interactive, immersive and collaborative learning environments that simulate real-world experiences. While VR is increasingly used in dental education, research on fully immersive metaverse-based learning remains limited.Methods In this pilot study, a custom metaverse environment was developed to teach TMJ concepts. Then, the effectiveness of conventional and metaverse-based teaching methods in improving dental students' understanding of the TMJ was evaluated experimentally. A randomised trial was conducted with 120 first-year dental students, divided into three groups: classical lecturing, metaverse-based training and a combination of both.Results Findings indicate that students in the metaverse and combined groups outperformed those in the classical lecturing group, with no significant difference between the two metaverse-involved groups.Conclusions This suggests that for highly complex anatomical structures like the TMJ, metaverse-based training alone may be sufficient, eliminating the need for additional traditional instruction. The study highlights the metaverse's potential to enhance dental education by providing a fully 3D, interactive learning experience.Book Part Artificial Intelligence in Dentistry(CRC Press, 2025) Cagiltay, Nergiz Ercil; Kılıçarslan, Mehmet Ali; Basmaci, FulyaToday, with advanced technologies, collecting detailed and big data from the environment and analyzing it using intelligent techniques has become possible, providing important insights into phenomena as well as future predictions. Big data is characterized by its high volume, velocity, and variety. Here, the volume is the amount and size of the data, which is measured in terabytes, petabytes, exabytes, or zettabytes. Velocity is the offered form of big data, which can be batch, near-real-time, real-time, or streaming. Finally, variety is the structure of the big data, which can be structured, such as in relational or dimensional models, as in warehouses, or unstructured, which is stored without any organization. It can also be in semi-structured form, where the data is unstructured but there is some meta-data or some tags for describing the data. Today, these forms of data are being collected for different dental purposes in several formats, such as images, raw data, or coordinates. © 2025 Elsevier B.V., All rights reserved.Article Citation - WoS: 3Citation - Scopus: 2Evaluation of the Effects of Avatar on Learning Temporomandibular Joint in a Metaverse-Based Training(John Wiley and Sons Inc, 2024) Basmaci, Fulya; Bulut, Ali Can; Ozcelik, Erol; Ekici, Saliha Zerdali; Kilicarslan, Mehmet Ali; Cagiltay, Nergiz Ercil; Zerdali Ekici, SalihaPurposeAvatars, representing users in the digital world, can influence users' behavior and attitudes. This study evaluates the impact of representing dental students receiving temporomandibular joint (TMJ) education in the metaverse via an anonymous or identified avatar.MethodsParticipants included 80 dental students in their fourth and fifth years of study. They were randomly assigned to either the avatar group (identified avatar) or the control group (anonymous avatar). Prior to training, participants completed a demographic questionnaire and a pretraining knowledge assessment. TMJ training was conducted in the metaverse for both groups. Pre- and post-training assessments included the Spielberger State-Trait Anxiety Inventory and a shyness scale to ensure group comparability. A post-test consisting of five questions was administered to both groups after 2 weeks of training.ResultsThere were no significant differences in pretraining scores for prior knowledge (p = 0.67), trait anxiety (p = 0.28), state anxiety (p = 0.92), or shyness (p = 0.42) between the avatar and control groups, indicating comparability at baseline. Post-training analysis revealed significantly higher post-test scores in the avatar group (median = 80) compared to the control group (median = 60) (p = 0.03).ConclusionsMetaverse environments offer various benefits for students, educators, and educational institutions in health education programs. Representing learners and their identities in training environments can enhance learning outcomes.Article Citation - WoS: 3Citation - Scopus: 3Expectancy From, and Acceptance of Augmented Reality in Dental Education Programs: a Structural Equation Model(Wiley, 2024) Toker, Sacip; Akay, Canan; Basmaci, Fulya; Kilicarslan, Mehmet Ali; Mumcu, Emre; Cagiltay, Nergiz ErcilObjectiveDental schools need hands-on training and feedback. Augmented reality (AR) and virtual reality (VR) technologies enable remote work and training. Education programs only partially integrated these technologies. For better technology integration, infrastructure readiness, prior-knowledge readiness, expectations, and learner attitudes toward AR and VR technologies must be understood together. Thus, this study creates a structural equation model to understand how these factors affect dental students' technology use.MethodsA correlational survey was done. Four questionnaires were sent to 755 dental students from three schools. These participants were convenience-sampled. Surveys were developed using validity tests like explanatory and confirmatory factor analyses, Cronbach's alpha, and composite reliability. Ten primary research hypotheses are tested with path analysis.ResultsA total of 81.22% responded to the survey (755 out of 930). Positive AR attitude, expectancy, and acceptance were endogenous variables. Positive attitudes toward AR were significantly influenced by two exogenous variables: infrastructure readiness (B = 0.359, beta = 0.386, L = 0.305, U = 0.457, p = 0.002) and prior-knowledge readiness (B = -0.056, beta = 0.306, L = 0.305, U = 0.457, p = 0.002). Expectancy from AR was affected by infrastructure, prior knowledge, and positive and negative AR attitudes. Infrastructure, prior-knowledge readiness, and positive attitude toward AR had positive effects on expectancy from AR (B = 0.201, beta = 0.204, L = 0.140, U = 0.267, p = 0.002). Negative attitude had a negative impact (B = -0.056, beta = -0.054, L = 0.091, U = 0.182, p = 0.002). Another exogenous variable was AR acceptance, which was affected by infrastructure, prior-knowledge preparation, positive attitudes, and expectancy. Significant differences were found in infrastructure, prior-knowledge readiness, positive attitude toward AR, and expectancy from AR (B = 0.041, beta = 0.046, L = 0.026, U = 0.086, p = 0.054).ConclusionInfrastructure and prior-knowledge readiness for AR significantly affect positive AR attitudes. Together, these three criteria boost AR's potential. Infrastructure readiness, prior-knowledge readiness, positive attitudes toward AR, and AR expectations all increase AR adoption. The study provides insights that can help instructional system designers, developers, dental education institutions, and program developers better integrate these technologies into dental education programs. Integration can improve dental students' hands-on experience and program performance by providing training options anywhere and anytime.Article Moocs and Economic Disadvantage: a Path Analysis of 3.5 Million Mitx Learners(Routledge Journals, Taylor & Francis Ltd, 2025) Cagiltay, Nergiz Ercil; Toker, Sacip; Cagiltay, KursatMassive Online Open Courses (MOOCs) are offered by universities and companies to provide quality education to anyone, anyplace and at any time. The impact of economic disadvantage on these courses has not been fully explored despite several studies. This study aimed to investigate the impact of country's income level on the success of 3,523,692 learners from 204 countries enrolled in 174 MITx MOOCs. The countries were classified as low- and lower-middle-income (L&LM) or high- and upper-middle-income (H&UM). A structural equation modelling with multigroup analysis conducted. The findings revealed that learners in the L&LM group performed better academically. Completion rates were 66% for L&LM and 25% for H&UM, and certification rates were 95% for L&LM and 99% for H&UM. This shows that L&LM learners may be more motivated because they believe MOOCs might help their careers. These results are essential for creating MOOCs that fit diverse learner demographics.Article Citation - WoS: 22Citation - Scopus: 37Performing and Analyzing Non-Formal Inspections of Entity Relationship Diagram (Erd)(Elsevier Science inc, 2013) Tokdemir, Gul; Kilic, Ozkan; Topalli, Damla; Cagiltay, Nergiz ErcilDesigning and understanding of diagrammatic representations is a critical issue for the success of software projects because diagrams in this field provide a collection of related information with various perceptual signs and they help software engineers to understand operational systems at different levels of information system development process. Entity relationship diagram (ERD) is one of the main diagrammatic representations of a conceptual data model that reflects users' data requirements in a database system. In today's business environment, the business model is in a constant change which creates highly dynamic data requirements which also requires additional processes like modifications of ERD. However, in the literature there are not many measures to better understand the behaviors of software engineers during designing and understanding these representations. Hence, the main motivation of this study is to develop measures to better understand performance of software engineers during their understanding process of ERD. Accordingly, this study proposes two measures for ERD defect detection process. The defect detection difficulty level (DF) measures how difficult a defect to be detected according to the other defects for a group of software engineers. Defect detection performance (PP) measure is also proposed to understand the performance of a software engineer during the defect detection process. The results of this study are validated through the eye tracker data collected during the defect detection process of participants. Additionally, a relationship between the defect detection performance (PP) of a software engineer and his/her search patterns within an ERD is analyzed. Second experiment with five participants is also conducted to show the correlation between the proposed metric results and eye tracker data. The results of experiment-2 also found to be similar for DF and PP values. The results of this study are expected to provide insights to the researchers, software companies, and to the educators to improve ERD reasoning process. Through these measures several design guidelines can be developed for better graphical representations and modeling of the information which would improve quality of these diagrams. Moreover, some reviewing instructions can be developed for the software engineers to improve their reviewing process in ERD. These guidelines in turn will provide some tools for the educators to improve design and review skills of future software engineers. (c) 2013 Elsevier Inc. All rights reserved.Conference Object Citation - WoS: 1Citation - Scopus: 4Patient Safety & Clinical Decision Support Systems (Cdss): a Case Study in Turkey(Ieee, 2015) Cagiltay, Nergiz Ercil; Tokdemir, Gul; Menekse, Gonca GokceDecision making process is crucial in several stages of clinical procedures. On the other hand, there are not many studies showing the implications of decision support systems in clinical environments. Hence, adaptation of Decision Support Systems to clinical environment is getting more important as we can collect more data through sensors and yet cannot use it effectively in decision making process. This study aims to understand the effects, benefits and obstacles utilizing CDSS in healthcare. For this purpose, 60 CDSS studies were analyzed to better understand their purpose, implementation domain, and success degrees in the world. Also, a case study was made for analyzing the situation in Turkey. The results show that in the field of neurosurgery, the level of analysis of neurosurgical data in Turkey is very low. The results show an urgent need for collaboration of IT experts and medical authorities to better record and analyze clinical data in the field of neurosurgery.Conference Object Citation - WoS: 6Citation - Scopus: 8Simulation-Based Environments for Surgical Practice(Ieee, 2017) Cagiltay, Nergiz Ercil; Ozcelik, Erol; Maras, Hakan; Dalveren, Gonca Gokce MenekseModeling and simulation environments provide several insights about the real situations such as endoscopic surgery. Endoscopic surgery requires both hand skills, so, understanding the effect of using dominant or non dominant hand on mental workload is important to better design, develop and implement modeling and simulation environments to support real-life implementations of surgical procedures. This experimental study presents a simulation application of eye-tracking approach to understand mental workload in different hand conditions: dominant hand, non-dominant hand and both hand. The results of the study show that, performing simulated surgical tasks by both hands compared to dominant hand, increases mental workload which is evident by higher pupil size. Accordingly, to manage the mental-load problems of surgeons while performing complex tasks that require both hand usage simulation-based environments can be used. Consequently, collection of detailed information such as eye-data, can give several insights about the behaviors of the surgeons. Also, their required skills can be improved by development of simulation and training environments.Article Citation - WoS: 23Citation - Scopus: 27Insights From Pupil Size To Mental Workload of Surgical Residents: Feasibility of an Educational Computer-Based Surgical Simulation Environment (Ece) Considering the Hand Condition(Sage Publications inc, 2018) Cagiltay, Nergiz Ercil; Ozcelik, Erol; Maras, Hakan; Dalveren, Gonca Gokce Menekse; Menekse Dalveren, Gonca GokceThe advantage of simulation environments is that they present various insights into real situations, where experimental research opportunities are very limited-for example, in endoscopic surgery. These operations require simultaneous use of both hands. For this reason, surgical residents need to develop several motor skills, such as eye-hand coordination and left-right hand coordination. While performing these tasks, the hand condition (dominant, nondominant, both hands) creates different degrees of mental workload, which can be assessed through mental physiological measures-namely, pupil size. Studies show that pupil size grows in direct proportion to mental workload. However, in the literature, there are very limited studies exploring this workload through the pupil sizes of the surgical residents under different hand conditions. Therefore, in this study, we present a computer-based simulation of a surgical task using eye-tracking technology to better understand the influence of the hand condition on the performance of skill-based surgical tasks in a computer-based simulated environment. The results show that under the both-hand condition, the pupil size of the surgical residents is larger than the one under the dominant and nondominant hand conditions. This indicates that when the computer-simulated surgical task is performed with both hands, it is considered more difficult than in the dominant and nondominant hand conditions. In conclusion, this study shows that pupil size measurements are sufficiently feasible to estimate the mental workload of the participants while performing surgical tasks. The results of this study can be used as a guide by instructional system designers of skill-based training programs.Article Citation - WoS: 16Citation - Scopus: 15Construct and Face Validity of the Educational Computer-Based Environment (Ece) Assessment Scenarios for Basic Endoneurosurgery Skills(Springer, 2017) Ozcelik, Erol; Sengul, Gokhan; Berker, Mustafa; Cagiltay, Nergiz ErcilBackground In neurosurgery education, there is a paradigm shift from time-based training to criterion-based model for which competency and assessment becomes very critical. Even virtual reality simulators provide alternatives to improve education and assessment in neurosurgery programs and allow for several objective assessment measures, there are not many tools for assessing the overall performance of trainees. This study aims to develop and validate a tool for assessing the overall performance of participants in a simulation-based endoneurosurgery training environment. Methods A training program was developed in two levels: endoscopy practice and beginning surgical practice based on four scenarios. Then, three experiments were conducted with three corresponding groups of participants (Experiment 1, 45 (32 beginners, 13 experienced), Experiment 2, 53 (40 beginners, 13 experienced), and Experiment 3, 26 (14 novices, 12 intermediate) participants). The results analyzed to understand the common factors among the performance measurements of these experiments. Then, a factor capable of assessing the overall skill levels of surgical residents was extracted. Afterwards, the proposed measure was tested to estimate the experience levels of the participants. Finally, the level of realism of these educational scenarios was assessed. Results The factor formed by time, distance, and accuracy on simulated tasks provided an overall performance indicator. The prediction correctness was very high for the beginners than the one for experienced surgeons in Experiments 1 and 2. When non-dominant hand is used in a surgical procedure-based scenario, skill levels of surgeons can be better predicted. The results indicate that the scenarios in Experiments 1 and 2 can be used as an assessment tool for the beginners, and scenario-2 in Experiment 3 can be used as an assessment tool for intermediate and novice levels. It can be concluded that forming the balance between perceived action capacities and skills is critical for better designing and developing skill assessment surgical simulation tools.