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Article Citation - WoS: 10Citation - Scopus: 12Distinguishing Intermediate and Novice Surgeons by Eye Movements(Frontiers Media Sa, 2020) Menekse Dalveren, Gonca Gokce; Cagiltay, Nergiz ErcilSurgical skill-level assessment is key to collecting the required feedback and adapting the educational programs accordingly. Currently, these assessments for the minimal invasive surgery programs are primarily based on subjective methods, and there is no consensus on skill level classifications. One of the most detailed of these classifications categorize skill levels as beginner, novice, intermediate, sub-expert, and expert. To properly integrate skill assessment into minimal invasive surgical education programs and provide skill-based training alternatives, it is necessary to classify the skill levels in as detailed a way as possible and identify the differences between all skill levels in an objective manner. Yet, despite the existence of very encouraging results in the literature, most of the studies have been conducted to better understand the differences between novice and expert surgical skill levels leaving out the other crucial skill levels between them. Additionally, there are very limited studies by considering the eye-movement behaviors of surgical residents. To this end, the present study attempted to distinguish novice- and intermediate-level surgical residents based on their eye movements. The eye-movement data was recorded from 23 volunteer surgical residents while they were performing four computer-based simulated surgical tasks under different hand conditions. The data was analyzed using logistic regression to estimate the skill levels of both groups. The best results of the estimation revealing a 91.3% recognition rate of predicting novice and intermediate surgical residents on one scenario were selected from four under the dominant hand condition. These results show that the eye-movements can be potentially used to identify surgeons with intermediate and novice skills. However, the results also indicate that the order in which the scenarios are provided, and the design of the scenario, the tasks, and their appropriateness with the skill levels of the participants are all critical factors to be considered in improving the estimation ratio, and hence require thorough assessment for future research.Article Citation - WoS: 6Citation - Scopus: 6Understanding the Effect of Handedness on Both-Handed Task Performance: an Experimental Study Based on a Haptic-Controlled, Simulation-Based Surgical Skill Training Scenario(Taylor & Francis inc, 2019) Topalli, Damla; Eyuboglu, Burak Gokberk; Cagiltay, Nergiz ErcilUnderstanding the performance on both-handed tasks, such as endoscopic surgery, is critical to better organize and develop appropriate instructional systems to improve the necessary skills of surgeons. However, in the literature, only a limited number of studies have investigated the effect of handedness on both-handed task performance. This study aimed to provide an understanding of the participants' performance differences while performing both-handed tasks through a haptic user interface in a simulated virtual environment specifically developed for surgical training purposes. Twenty-four surgeons attending a medical school in Turkey voluntarily participated in the study. The duration, accuracy, and collision measures were automatically recorded by software. The results revealed that the left-handed participants performed the both-handed tasks (camera: nondominant hand, tool: dominant-hand) in a significantly shorter time than the right-handed participants. This study also showed that haptic-controlled simulation-based surgical skill training systems can potentially provide measures for better understanding the individual behaviors and deliver alternative training environments specific to individual requirements.Article Citation - WoS: 53Investigation of Emerging Trends in the E-Learning Field Using Latent Dirichlet Allocation(Athabasca Univ Press, 2021) Gurcan, Fatih; Ozyurt, Ozcan; Cagiltay, Nergiz ErcilE-learning studies are becoming very important today as they provide alternatives and support to all types of teaching and learning programs. The effect of the COVID-19 pandemic on educational systems has further increased the significance of e-learning. Accordingly, gaining a full understanding of the general topics and trends in e-learning studies is critical for a deeper comprehension of the field. There are many studies that provide such a picture of the e-learning field, but the limitation is that they do not examine the field as a whole. This study aimed to investigate the emerging trends in the e-learning field by implementing a topic modeling analysis based on latent Dirichlet allocation (LDA) on 41,925 peer-reviewed journal articles published between 2000 and 2019. The analysis revealed 16 topics reflecting emerging trends and developments in the e-learning field. Among these, the topics "MOOC," "learning assessment," and "elearning systems" were found to be key topics in the field, with a consistently high volume. In addition, the topics of "learning algorithms," "learning factors," and "adaptive learning" were observed to have the highest overall acceleration, with the first two identified as having a higher acceleration in recent years. Going by these results, it is concluded that the next decade of e-learning studies will focus on learning factors and algorithms, which will possibly create a baseline for more individualized and adaptive mobile platforms. In other words, after a certain maturity level is reached by better understanding the learning process through these identified learning factors and algorithms, the next generation of e-learning systems will be built on individualized and adaptive learning environments. These insights could be useful for e-learning communities to improve their research efforts and their applications in the field accordingly.Article Citation - WoS: 20Citation - Scopus: 25Detecting Latent Topics and Trends in Software Engineering Research Since 1980 Using Probabilistic Topic Modeling(Ieee-inst Electrical Electronics Engineers inc, 2022) Gurcan, Fatih; Dalveren, Gonca Gokce Menekse; Cagiltay, Nergiz Ercil; Soylu, AhmetThe landscape of software engineering research has changed significantly from one year to the next in line with industrial needs and trends. Therefore, today's research literature on software engineering has a rich and multidisciplinary content that includes a large number of studies; however, not many of them demonstrate a holistic view of the field. From this perspective, this study aimed to reveal a holistic view that reflects topics, trends, and trajectories in software engineering research by analyzing the majority of domain-specific articles published over the last 40 years. This study first presents an objective and systematic method for corpus creation through major publication sources in the field. A corpus was then created using this method, which includes 44 domain-specific conferences and journals and 57,174 articles published between 1980 and 2019. Next, this corpus was analyzed using an automated text-mining methodology based on a probabilistic topic-modeling approach. As a result of this analysis, 24 main topics were found. In addition, topical trends in the field were revealed. Finally, three main developmental stages of the field were identified as: the programming age, the software development age, and the software optimization age.Article Citation - WoS: 31Citation - Scopus: 40Research Trends on Distance Learning: a Text Mining-Based Literature Review From 2008 To 2018(Routledge Journals, Taylor & Francis Ltd, 2023) Gurcan, Fatih; Cagiltay, Nergiz ErcilToday's dynamic distance learning environments offer a flexible, comfortable, and lifelong learning experience, independent of space and time. In this way, it also supports and develops existing traditional training programs. The increasing importance of knowledge, skills and learning in today's technological life cycle has led to an increase and diversification of research and applications in distance learning. Accordingly, distance learning literature has a rich content supported by a multidisciplinary background. From this point of view, it is crucial to perceive the research landscape reflecting the general themes and trends studied in the field of distance learning. This study aims at revealing the distance learning research themes and trends by analyzing the 27,735 articles of journal conducted in the last decade. The methodology of the study is based on semantic content analysis implemented by N-gram-based text categorization technique. As a result, 10 main themes are discovered, namely, "System establishment", "Media", "Assessment", "Method", "Content", "Education levels", "Learner", "Research methods", "Interaction-Communication", and "Resource-Material-Tool". In this context, the findings of the study are expected to provide significant insights to guide prospective research and practice in the field and to develop continuous improvements and standards for distance education communities.Article A User Task Design Notation for Improved Software Design(Peerj inc, 2021) Ozcan, Eda; Topalli, Damla; Tokdemir, Gul; Cagiltay, Nergiz ErcilSystem design is recognized as one of the most critical components of a software system that bridges system requirements and coding. System design also has a significant impact on testing and maintenance activities, and on further improvements during the lifespan of the software system. Software design should reflect all necessary components of the requirements in a clear and understandable manner by all stakeholders of the software system. To distinguish system elements, separation of concerns in software design is suggested. In this respect, identification of the user tasks, i.e., the tasks that need to be performed by the user, is not currently reflected explicitly in system design documents. Our main assumption in this study is that software quality can be improved significantly by clearly identifying the user tasks from those that need to be performed by the computer system itself. Additionally, what we propose has the potential to better reflect the user requirements and main objectives of the system on the software design and thereby to improve software quality. The main aim of this study is to introduce a novel notation for software developers in the frame of UML Activity Diagram (UML-AD) that enables designers to identify the user tasks and define them separately from the system tasks. For this purpose, an extension of UML-AD, named UML-ADE (UML-Activity Diagram Extended) was proposed. Afterwards, it was implemented in a serious game case for which the specification of user tasks is extremely important. Finally, its effectiveness was analyzed and compared to UML-AD experimentally with 72 participants. The defect detection performance of the participants on both diagrams with two real-life serious game scenarios was evaluated. Results show a higher level of understandability for those using UML-ADE, which in turn may indicate a better design and higher software quality. The results encourage researchers to develop specific design representations dedicated to task design to improve system quality and to conduct further evaluations of the impact of these design on each of the above mentioned potential benefits for the software systems.Article Citation - WoS: 26Citation - Scopus: 36Exploratory Analysis of Topic Interests and Their Evolution in Bioinformatics Research Using Semantic Text Mining and Probabilistic Topic Modeling(Ieee-inst Electrical Electronics Engineers inc, 2022) Gurcan, Fatih; Cagiltay, Nergiz ErcilBioinformatics, which has developed rapidly in recent years with the collaborative contributions of the fields of biology and informatics, provides a deeper perspective on the analysis and understanding of complex biological data. In this regard, bioinformatics has an interdisciplinary background and a rich literature in terms of domain-specific studies. Providing a holistic picture of bioinformatics research by analyzing the major topics and their trends and developmental stages is critical for an understanding of the field. From this perspective, this study aimed to analyze the last 50 years of bioinformatics studies (a total of 71,490 articles) by using an automated text-mining methodology based on probabilistic topic modeling to reveal the main topics, trends, and the evolution of the field. As a result, 24 major topics that reflect the focuses and trends of the field were identified. Based on the discovered topics and their temporal tendencies from 1970 until 2020, the developmental periods of the field were divided into seven phases, from the "newborn" to the "wisdom" stages. Moreover, the findings indicated a recent increase in the popularity of the topics "Statistical Estimation", "Data Analysis Tools", "Genomic Data", "Gene Expression", and "Prediction". The results of the study revealed that, in bioinformatics studies, interest in innovative computing and data analysis methods based on artificial intelligence and machine learning has gradually increased, thereby marking a significant improvement in contemporary analysis tools and techniques based on prediction.Article Citation - WoS: 77Citation - Scopus: 107Teaching Software Engineering by Means of Computer-Game Development: Challenges and Opportunities(Wiley, 2007) Cagiltay, Nergiz ErcilSoftware-engineering education programs are intended to prepare students for a field that involves rapidly changing conditions and expectations. Thus, there is always a danger that the skills and the knowledge provided may soon become obsolete. This paper describes results and draws on experiences from the implementation of a computer game-development course whose design addresses problems in software-engineering education by improving students' abilities in four areas: (1) problem solving; (2) the application of previously learned knowledge; (3) the use of independent learning; and (4) learning by doing. In order to better understand this course's effect on students' performance in a software-development project, I investigated 125 students' performance in a 1-year senior-project course. Results of this study show that the students who had taken the computer game-development course became more successful in the senior-project course than the students who had not taken it.Article Citation - WoS: 16Citation - Scopus: 26Evolution of Software Testing Strategies and Trends: Semantic Content Analysis of Software Research Corpus of the Last 40 Years(Ieee-inst Electrical Electronics Engineers inc, 2022) Gurcan, Fatih; Dalveren, Gonca Gokce Menekse; Cagiltay, Nergiz Ercil; Roman, Dumitru; Soylu, AhmetFrom the early days of computer systems to the present, software testing has been considered as a crucial process that directly affects the quality and reliability of software-oriented products and services. Accordingly, there is a huge amount of literature regarding the improvement of software testing approaches. However, there are limited reviews that show the whole picture of the software testing studies covering the topics and trends of the field. This study aims to provide a general figure reflecting topics and trends of software testing by analyzing the majority of software testing articles published in the last 40 years. A semi-automated methodology is developed for the analysis of software testing corpus created from core publication sources. The methodology of the study is based on the implementation of probabilistic topic modeling approach to discover hidden semantic patterns in the 14,684 published articles addressing software testing issues between 1980 and 2019. The results revealed 42 topics of the field, highlighting five software development ages, namely specification, detection, generation, evaluation, and prediction. The recent accelerations of the topics also showed a trend toward prediction-based software testing actions. Additionally, a higher trend on the topics concerning "Security Vulnerability", "Open Source" and "Mobile Application" was identified. This study showed that the current trend of software testing is towards prediction-based testing strategies. Therefore, the findings of this study may provide valuable insights for the industry and software communities to be prepared for the possible changes in the software testing procedures using prediction-based approaches.Article Citation - WoS: 4Citation - Scopus: 10Exploring the Influence of Countries' Economic Conditions on Massive Open Online Course (Mooc) Participation: a Study of 3.5 Million Mitx Learners(Athabasca Univ Press, 2023) Cagiltay, Nergiz Ercil; Toker, Sacip; Cagiltay, KursatIt is well known that there are disparities in access to education around the world, with developed countries generally having better educational resources and opportunities compared to developing countries. Massive open online courses (MOOCs) have been proposed as a way to bridge this gap by providing free or low-cost online education to anyone with an Internet connection. This study aimed to better understand the effects of location, both country and region, on the use of MOOCs, using data from 3.5 million learners who registered for MOOCs offered by the Massachusetts Institute of Technology (MIT). The data set provided a broad picture of how MOOCs are being used around the globe. The results of the study indicated significant differences in the use of MOOCs among students from different countries and their corresponding economic levels. In order to address these differences and improve access to education through MOOCs, the study suggested several actions that could be taken. These include providing better infrastructure and support for MOOC learners in developing countries, increasing awareness of and access to MOOCs in these regions, and working to improve the quality and relevance of MOOC offerings. Overall, the study highlighted the potential of MOOCs to bridge the educational gap between developed and developing countries, but also emphasized the need for continued efforts to remove barriers and improve access to these resources.
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