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Article Citation - WoS: 27Citation - Scopus: 43Digital Transformation Strategies, Practices, and Trends: a Large-Scale Retrospective Study Based on Machine Learning(Mdpi, 2023) Gurcan, Fatih; Boztas, Gizem Dilan; Dalveren, Gonca Gokce Menekse; Derawi, MohammadThe purpose of this research is to identify the areas of interest, research topics, and application areas that reflect the research nature of digital transformation (DT), as well as the strategies, practices, and trends of DT. To accomplish this, the Latent Dirichlet allocation algorithm, a probabilistic topic modeling technique, was applied to 5350 peer-reviewed journal articles on DT published in the last ten years, from 2013 to 2022. The analysis resulted in the discovery of 34 topics. These topics were classified, and a systematic taxonomy for DT was presented, including four sub-categories: implementation, technology, process, and human. As a result of time-based trend analysis, "Sustainable Energy", "DT in Health", "E-Government", "DT in Education", and "Supply Chain" emerged as top topics with an increasing trend. Our findings indicate that research interests are focused on specific applications of digital transformation in industrial and public settings. Based on our findings, we anticipate that the next phase of DT research and practice will concentrate on specific DT applications in government, health, education, and economics. "Sustainable Energy" and "Supply Chain" have been identified as the most prominent topics in current DT processes and applications. This study can help researchers and practitioners in the field by providing insights and implications about the evolution and applications of DT. Our findings are intended to serve as a guide for DT in understanding current research gaps and potential future research topics.Conference Object Citation - WoS: 2Citation - Scopus: 2Software Engineering in Medical Informatics: a Systematic Literature Review(Assoc Computing Machinery, 2019) Dalveren, Gonca Gokce Menekse; Mishra, DeeptiThis study presents a systematic literature review to provide overall view of the application of Software Engineering (SE) in Medical Informatics (MI) field. Articles published from 2010 to 2019 from seven selected databases ( Emerald, PubMed, IEEE, ACM, Taylor Francis, SAGE and Wiley) were investigated. The existing literature was analyzed, and the emerging areas of research in the medical informatics field have been identified. According to the findings of this study, medical informatics research has been applied in many fields but there is still potential of further research in different areas. Most of the reviewed studies were conducted on data mining, decision support, deep learning and IoT. Also, it can be said that most of the applications are provided as web-based instead of mobile applications. To conclude, the results of this study provides insights to the researchers about the research directions and the gaps in the literature in the MI and SE fields.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: 16Citation - Scopus: 15Using Eye-Movement Events To Determine the Mental Workload of Surgical Residents(int Group Eye Movement Research, 2018) Dalveren, Gonca Gokce Menekse; Cagiltay, Nergiz ErcilThese days, eye-tracking is one of the promising technologies used in different fields such as aviation, arts, sports, psychology and driving for several purposes. Even though it is being used for health purposes, studies involving eye-tracking are rare in the field of endo-neurosurgery. This study aims to use this technology to promote our understanding of the effect related to computer-based instructional materials on mental workload of endo-neurosurgery residents. Four computer-based simulation scenarios are developed based on skill development requirements of endo-neurosurgery residents. Two of them were designed as general models and the other two as simulated surgical models. During these surgery procedures, in real settings, surgical residents need to use their both hands simultaneously to control the endoscope and the operational tool in a coordinated fashion. Therefore, to shed light on the participants' behaviors, these scenarios are performed with dominant-hand, non-dominant hand and, finally with both-hands using haptic interfaces. Twenty-three residents volunteered in this study. Their eye-movements were recorded while performing the scenarios. According to the results of this study, when performing the simulated surgical models, an increase in the participants' mental workload was recorded when compared to the other scenarios. Accordingly, it can be concluded that the eye-movements of surgical residents can provide insights about the anticipated level of difficulty about the skill-based tasks. This information might be very critical to properly design and organize instructional materials for endo-neurosurgery, and also to better guide and evaluate the progress of trainees in computer simulation-based skill training environments.Article Citation - WoS: 6Citation - Scopus: 7Are Left- and Right-Eye Pupil Sizes Always Equal?(int Group Eye Movement Research, 2019) Cagiltay, Nergiz Ercil; Dalveren, Gonca Gokce MenekseEye movements provide very critical information about the cognitive load and behaviors of human beings. Earlier studies report that under normal conditions, the left- and right-eye pupil sizes are equal. For this reason, most studies undertaking eye-movement analysis are conducted by only considering the pupil size of a single eye or taking the average size of both eye pupils. This study attempts to offer a better understanding concerning whether there are any differences between the left- and right-eye pupil sizes of the right-handed surgical residents while performing surgical tasks in a computer-based simulation environment under different conditions (left-hand, right-hand and both hands). According to the results, in many cases, the right-eye pupil sizes of the participants were larger than their left-eye pupil sizes while performing the tasks under right-hand and both hands conditions. However, no significant difference was found in relation to the tasks performed under left-hand condition in all scenarios. These results are very critical to shed further light on the cognitive load of the surgical residents by analyzing their left-eye and right-eye pupil sizes. Further research is required to investigate the effect of the difficulty level of each scenario, its appropriateness with the skill level of the participants, and handedness on the differences between the leftand right-eye pupil sizes.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: 1Citation - Scopus: 4Structured Srs for E-Government Services With Boilerplate Design and Interface(Ieee-inst Electrical Electronics Engineers inc, 2023) Oztekin, Gonca Canan; Dalveren, Gonca Gokce MenekseThere 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 Group Discussion in a Blended Environment in Engineering Education(Uikten - Assoc information Communication Technology Education & Science, 2021) Mishra, Deepti; Dalveren, Gonca Gokce Menekse; Volden, Frode S.; Allen, Carly GraceGroup work is a necessary element of engineering education and group members need information about one another, group process, shared attention and mutual understanding during group discussions. There are several important elements for establishing and maintaining a group discussion such as participant's role, seating arrangement, verbal and non-verbal cues, eye gaze, gestures etc. The present study investigates these elements for identifying the behavior of group members in a blend of traditional face-to-face discussion along with computer supported cooperative work (CSCW) setting. The results of this study have shown that, speaking duration is the key factor for identifying the leadership in a group and participants mostly used eye gazes for turn taking. Although this study is a mix of face-to-face and CSCW discussion setting, participants mostly behave like face-to-face group discussion. However, unlike the previous studies involving face-to-face discussion, the relation between seating arrangement and amount of attention is not apparent from the data during this study.Article Citation - WoS: 9Citation - Scopus: 20Business 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, MohammadThe 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: 20Citation - Scopus: 27Career in Cloud Computing: Exploratory Analysis of In-Demand Competency Areas and Skill Sets(Mdpi, 2022) Ozyurt, Ozcan; Gurcan, Fatih; Dalveren, Gonca Gokce Menekse; Derawi, MohammadThis study aims to investigate up-to-date career opportunities and in-demand competence areas and skill sets for cloud computing (CC), which plays a crucial role in the rapidly developing teleworking environments with the COVID-19 pandemic. In this paper, we conducted a semantic content analysis on 10,161 CC job postings using semi-automated text-mining and probabilistic topic-modeling procedures to discover the competency areas and skill sets as semantic topics. Our findings revealed 22 competency areas and 46 skills, which reflect the interdisciplinary background of CC jobs. The top five competency areas for CC were identified as "Engineering", "Development", "Security", "Architecture", and "Management". Besides, the top three skills emerged as "Communication Skills", "DevOps Tools", and "Software Development". Considering the findings, a competency-skill map was created that illustrates the correlations between CC competency areas and their related skills. Although there are many studies on CC, the competency areas and skill sets required to deal with cloud computing have not yet been empirically studied. Our findings can contribute to CC candidates and professionals, IT organizations, and academic institutions in understanding, evaluating, and developing the competencies and skills needed in the CC industry.
