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  • Article
    Citation - WoS: 8
    Citation - Scopus: 10
    Evaluation of Ten Open-Source Eye-Movement Classification Algorithms in Simulated Surgical Scenarios
    (Ieee-inst Electrical Electronics Engineers inc, 2019) Dalveren, Gonca Gokce Menekse; Cagiltay, Nergiz Ercil
    Despite providing several insights into visual attention and evidence regarding certain brain states and psychological functions, classifying eye movements is a highly demanding process. Currently, there are several algorithms to classify eye movement events which use different approaches. However, to date, only a limited number of studies have assessed these algorithms under specific conditions, such as those required for surgical training programmes. This study presents an investigation of ten open-source eye-movement classification algorithms using the Eye Tribe eye-tracker. The algorithms were tested on the eye-movement records obtained from 23 surgical residents, who performed computer-based surgical simulation tasks under different hand conditions. The aim was to offer data for the improvement of surgical training programmes. According to the results, due to the different classification methods and default threshold values, the ten algorithms produced different results. Considering the fixation duration, the only common event for all of the investigated algorithms, the binocular-individual threshold (BIT) algorithm resulted in a different clustering compared to the other algorithms. Based on the other set of common events, three clusters were determined by eight algorithms (except BIT and event detection (ED)), distinguishing dispersion-based, velocity-based and modified versions of velocity-based algorithms. Accordingly, it was concluded that dispersion-based and velocity-based algorithms provided different results. Additionally, as it individually specifies the threshold values for the eye-movement data, when there is no consensus about the threshold values to be set, the BIT algorithm can be selected. Especially for such cases like simulation-based surgical skill-training, the use of individualised threshold values in the BIT algorithm can be more beneficial in classifying the raw eye data and thus evaluating the individual progress levels of trainees based on their eye movement behaviours. In conclusion, the threshold values had a critical effect on the algorithm results. Since default values may not always be suitable for the unique features of different data sets, guidelines should be developed to indicate how the threshold values are set for each algorithm.
  • Article
    Citation - WoS: 22
    Citation - Scopus: 34
    An Analysis of Course Characteristics, Learner Characteristics, and Certification Rates in MITx MOOCs
    (Athabasca Univ Press, 2020) Cagiltay, Nergiz Ercil; Cagiltay, Kursat; Celik, Berkan; Software Engineering
    Massive Open Online Courses (MOOCs), capable of providing free (or low cost) courses for millions of learners anytime and anywhere, have gained the attention of researchers, educational institutions, and learners worldwide. Even though they provide several benefits, there are still some criticisms of MOOCs. For instance, MOOCs' high dropout rates or predominantly elite participation are considered to be important problems. In order to develop solutions for these problems, a deeper understanding of MOOCs is required. Today, despite the availability of several research studies about MOOCs, there is a shortage of in-depth research on course characteristics, learner characteristics, and predictors of certification rates. This study examined MOOC and learner characteristics in detail and explored the predictors of course certification rates based on data from 122 Massachusetts Institute of Technology MOOCs (MITx) on edX platform as well as data about the 2.8 million participants registered in these MOOCs. The results indicated that as the number of courses offered and the number of learners enrolled increased in years, there was a decrease in the certification rates among enrolled learners. According to our results, the number of average chapters completed, total forum messages, and mean age predicted course certification rates positively. On the other hand, the total number of chapters in a course predicted the course certification rates negatively. Based on these results, shorter and more interactive MOOCs are recommended by considering the needs of the learners, course content design, and strategies encouraging the enrolled students to enter the courses.
  • Article
    Citation - WoS: 53
    Investigation of Emerging Trends in the E-Learning Field Using Latent Dirichlet Allocation
    (Athabasca Univ Press, 2021) Gurcan, Fatih; Ozyurt, Ozcan; Cagiltay, Nergiz Ercil
    E-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: 20
    Citation - Scopus: 25
    Detecting 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, Ahmet
    The 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: 17
    Citation - Scopus: 22
    Seven Principles of Instructional Content Design for a Remote Laboratory: a Case Study on Errl
    (Ieee-inst Electrical Electronics Engineers inc, 2011) Cagiltay, Nergiz Ercil; Aydin, Elif; Aydin, Cansu Cigdem; Kara, Ali; Alexandru, Marian
    This paper discusses the results of a study of the requirements for developing a remote radio frequency (RF) laboratory for electrical engineering students. It investigates students' preferred usage of the technical content of a state-of-the-art RF laboratory. The results of this study are compared to previous findings, which dealt with other user groups (technicians in technical colleges and engineers in the RF domain). Based on the results of these analyses, seven essential principles for designing and developing such a laboratory were identified. As a case study, these principles were then implemented into a remote laboratory system. In this paper, the implementation examples are also provided and discussed. The primary aim of this study is to guide remote laboratory platform developers toward the most effective instructional design. This study also determined, from the remote laboratory system case study, what the requirements are of such a laboratory from the students' perspective.
  • Article
    Citation - WoS: 2
    Citation - Scopus: 4
    Mobile Application Software Requirements Specification From Consumption Values
    (Mdpi, 2023) Derawi, Mohammad; Dalveren, Gonca Gokce Menekse; Cagiltay, Nergiz Ercil
    In today's society, mobile applications are becoming more popular and providing several advantages. However, users will resist using a product regardless of how well-tested or solid it is if the wrong requirements are implemented. Understanding the factors that influence the purchase of mobile applications can provide useful information for mobile application design and development. Hence, the purpose of this research is to better understand the impact of consumption values on customers in order to identify the software requirements for a mobile application. This study analyzes the possible behavioral changes of similar groups of university students in a five-year period. For this purpose, a questionnaire is administered to engineering faculty students in 2017 (46 females and 66 males) and 2021 (45 females and 90 males) to better understand customer behavioral changes. The findings highlight the significance of conditional value in customer behavior when purchasing mobile applications. Even though the other consumption values were found to have a negligible effect, there is some evidence indicating that the impact of consumption values on different target customer groups may vary considering their gender and familiarity with apps. Further research needs to be conducted to better understand the possible impact of age, cultural differences, education levels, and special considerations such as visually impaired people. Therefore, this study encourages mobile application designers and developers to raise awareness for the effect of consumption values such as conditional value on their customers' mobile application purchasing behaviors. The possible impact of the consumption values needs to be deeply understood, specifically for the target customer groups, and it should be considered in the software requirements specification (SRS), which is one of the important principles that allow software under consideration for development to function. As a result, a better understanding of consumption values will help developers design and develop better applications by specifying software requirements and marketing strategies.
  • Article
    Citation - WoS: 4
    Citation - Scopus: 10
    Exploring 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, Kursat
    It 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.
  • Article
    A User Task Design Notation for Improved Software Design
    (Peerj inc, 2021) Ozcan, Eda; Topalli, Damla; Tokdemir, Gul; Cagiltay, Nergiz Ercil
    System 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: 90
    Citation - Scopus: 132
    Big Data Software Engineering: Analysis of Knowledge Domains and Skill Sets Using Lda-Based Topic Modeling
    (Ieee-inst Electrical Electronics Engineers inc, 2019) Gurcan, Fatih; Cagiltay, Nergiz Ercil
    Software engineering is a data-driven discipline and an integral part of data science. The introduction of big data systems has led to a great transformation in the architecture, methodologies, knowledge domains, and skills related to software engineering. Accordingly, education programs are now required to adapt themselves to up-to-date developments by first identifying the competencies concerning big data software engineering to meet the industrial needs and follow the latest trends. This paper aims to reveal the knowledge domains and skill sets required for big data software engineering and develop a taxonomy by mapping these competencies. A semi-automatic methodology is proposed for the semantic analysis of the textual contents of online job advertisements related to big data software engineering. This methodology uses the latent Dirichlet allocation (LDA), a probabilistic topic-modeling technique to discover the hidden semantic structures from a given textual corpus. The output of this paper is a systematic competency map comprising the essential knowledge domains, skills, and tools for big data software engineering. The findings of this paper are expected to help evaluate and improve IT professionals' vocational knowledge and skills, identify professional roles and competencies in personnel recruitment processes of companies, and meet the skill requirements of the industry through software engineering education programs. Additionally, the proposed model can be extended to blogs, social networks, forums, and other online communities to allow automatic identification of emerging trends and generate contextual tags.
  • Article
    Citation - WoS: 23
    Citation - Scopus: 27
    Insights From Surgeons' Eye-Movement Data in a Virtual Simulation Surgical Training Environment: Effect of Experience Level and Hand Conditions
    (Taylor & Francis Ltd, 2018) Dalveren, Gonca Gokce Menekse; Cagiltay, Nergiz Ercil
    Today, with the advancements in the eye-tracking technology, it has become possible to follow surgeons' eye movements while performing surgical tasks. Despite the availability of studies providing a better understanding of surgeons' eye movements, research in the particular field of endoneurosurgery is very limited. Analysing surgeons' eye-movement data can provide general insights into how to improve surgical education programmes. In this study, four simulation-based task-oriented endoscopic surgery training scenarios were developed and implemented by 23 surgical residents using three different hand conditions; dominant, non-dominant, and both. The participants' recorded eye data comprised fixation number, fixation duration, saccade number, saccade duration, pursuit number, pursuit duration, and pupil size. This study has two main contributions: First, it reports on the eye-movement behaviours of surgical residents, demonstrating that novice residents tended to make more fixations and saccades than intermediate residents. They also had a higher fixation duration and followed the objects more frequently compared to the intermediates. Furthermore, hand conditions significantly affected the eye movements of the participants. Based on these results, it can be concluded that eye-movement data can be used to assess the skill levels of surgical residents and would be an important measure to better guide trainees in surgical education programmes. The second contribution of this study is the eye-movement event classifications of 10 different algorithms. Although the algorithms mostly provided similar results, there were a few conflicted values for some classifications, which offers a clue as to how researchers can utilise these algorithms with low sampling frequency eye trackers.