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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: 9Citation - Scopus: 21Business Intelligence Strategies, Best Practices, and Latest Trends: Analysis of Scientometric Data From 2003 To 2023 Using Machine Learning(Mdpi, 2023) Gurcan, Fatih; Ayaz, Ahmet; Dalveren, Gonca Gokce Menekse; Derawi, Mohammad; Menekse Dalveren, Gonca GokceThe widespread use of business intelligence products, services, and applications piques the interest of researchers in this field. The interest of researchers in business intelligence increases the number of studies significantly. Identifying domain-specific research patterns and trends is thus a significant research problem. This study employs a topic modeling approach to analyze domain-specific articles in order to identify research patterns and trends in the business intelligence field over the last 20 years. As a result, 36 topics were discovered that reflect the field's research landscape and trends. Topics such as "Organizational Capability", "AI Applications", "Data Mining", "Big Data Analytics", and "Visualization" have recently gained popularity. A systematic taxonomic map was also created, revealing the research background and BI perspectives based on the topics. This study may be useful to researchers and practitioners interested in learning about the most recent developments in the field. Topics generated by topic modeling can also be used to identify gaps in current research or potential future research directions.Article Citation - WoS: 2Citation - Scopus: 6Structured Srs for E-Government Services With Boilerplate Design and Interface(Ieee-inst Electrical Electronics Engineers inc, 2023) Oztekin, Gonca Canan; Dalveren, Gonca Gokce Menekse; Menekse Dalveren, Gonca GokceThere are many projects being carried out to develop e-Government applications. In order to develop an efficient application, a proper requirements specification is strictly required. However, in the case of improper requirements specifications, errors are unavoidable for the developed applications. Therefore, it is necessary to use a model to determine the quality of software requirements. In the literature, several studies have been presented to propose a quality model for software requirements. Yet, there is no study on the development of a quality model for software requirements in Turkish language. Thus, the purpose of this study is to propose a quality assessment model of Software Requirements Specification (SRS) in Turkish language for e-Government applications. The proposed model aims at defining common texts and confirming that the sentences used in writing SRS are developed within an assured structure in order to minimize and standardize the errors originating from natural language. For this purpose, a model based on the Rupp's boilerplate is created that allows the analyst or requirements engineer to accurately enter the requirements statements. In this study, an interface (webpage) is also created so that the model may match requirements with common text templates, compute similarity values, and also may insert the requirements, regulatory documents, and user requirements into the template in a more convenient format. In order to evaluate the proposed model, the sentences in the 32 documents, including 843 requirements, were adapted to the model. Then, the usability of the model was validated by the requirement engineers serving in a Government service. According to the results, it is concluded that the proposed model is applicable, and is able to improve the quality of SRS in Turkish language for e-Government applications.Article Citation - WoS: 16Citation - Scopus: 20The Effects of the Content Elements of Online Banner Ads on Visual Attention: Evidence From An-Eye Study(Mdpi, 2021) Peker, Serhat; Menekse Dalveren, Gonca Gokce; Inal, Yavuz; Dalveren, Gonca Gokce MenekseThe aim of this paper is to examine the influence of the content elements of online banner ads on customers' visual attention, and to evaluate the impacts of gender, discount rate and brand familiarity on this issue. An eye-tracking study with 34 participants (18 male and 16 female) was conducted, in which the participants were presented with eight types of online banner ads comprising three content elements-namely brand, discount rate and image-while their eye movements were recorded. The results showed that the image was the most attractive area among the three main content elements. Furthermore, the middle areas of the banners were noticed first, and areas located on the left side were mostly noticed earlier than those on the right side. The results also indicated that the discount areas of banners with higher discount rates were more attractive and eye-catching compared to those of banners with lower discount rates. In addition to these, the participants who were familiar with the brand mostly concentrated on the discount area, while those who were unfamiliar with the brand mostly paid attention to the image area. The findings from this study will assist marketers in creating more effective and efficient online banner ads that appeal to customers, ultimately fostering positive attitudes towards the advertisement.
