Köprüüstü simülatör uygulamaları ile teknik ve davranışsal becerilerin ölçülmesine yönelik model önerisi
A model proposal for evaluating technical and behavioral skills through bridge simulator practices
- Tez No: 1017599
- Danışmanlar: DR. ÖĞR. ÜYESİ ESMA UFLAZ, DOÇ. DR. ALİ CEM KUZU
- Tez Türü: Yüksek Lisans
- Konular: Denizcilik, Marine
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 2026
- Dil: Türkçe
- Üniversite: İstanbul Teknik Üniversitesi
- Enstitü: Lisansüstü Eğitim Enstitüsü
- Ana Bilim Dalı: Deniz Ulaştırma İşletme Mühendisliği Ana Bilim Dalı
- Bilim Dalı: Deniz Ulaştırma Mühendisliği Bilim Dalı
- Sayfa Sayısı: Belirtilmemiş.
Özet
Denizcilik eğitiminde köprüüstü simülatörleri, gemiinsanlarının teknik ve davranışsal becerilerini deniz koşullarına yakın bir ortamda edinmelerine ve geliştirmelerine olanak tanıyan temel araçlardan biri olarak kabul görmektedir. Gemiinsanlarının Eğitim, Belgelendirme ve Vardiya Tutma Standartları Hakkında Uluslararası Sözleşmesi (STCW) ve sektörel talepler çerçevesinde yürütülen simülatör uygulamalarına yönelik değerlendirmeler, yeterlilik tabanlı yaklaşımı esas almaktadır. Bununla birlikte, değerlendirme süreçlerinin standart kriterler çerçevesinde yapılandırılmasına karşın, değerlendiricilerin öznel yorumlarından kaynaklanan tutarsızlıklar hem literatürde hem de sektörel uygulamalarda giderek daha fazla dikkat çekmektedir. Bu çalışma; köprüüstü simülatör değerlendirmelerini daha nesnel, şeffaf ve uygulanabilir hale getirmek amacıyla, teknik ve davranışsal becerilerin simülatör uygulamaları değerlendirme sürecindeki belirleyicilik düzeyini ortaya koymaya yönelik bir model önerisi sunmaktadır. Bu amaç doğrultusunda STCW, IMO Model Kurs 7.01 ve 7.03, OCIMF ve INTERTANKO Davranışsal Beceri Değerlendirme ve Doğrulama Rehberi ile IAMU Simülatör Eğitimi Çalışma Grubu 2025 yılı raporu esas alınarak sekiz teknik (T1-T8) ve dokuz davranışsal (D1-D9) beceri belirlenmiştir. Söz konusu 17 beceri Bulanık TOPSIS yönteminde alternatif olarak konumlandırılmış; değerlendirme süreci üç kriter, senaryonun değerlendirme kriterlerine etkisi (K1), simülatör eğitimiyle geliştirilebilirlik (K2) ve ön bilgilendirmenin değerlendirme kriterlerine etkisi (K3), çerçevesinde yapılandırılmıştır. Çalışmanın veri toplama aşamasında, IMO Model Kurs 6.10 eğitimine haiz ve aktif olarak köprüüstü simülatör uygulamalarında değerlendirici olarak görev alan 10 kişilik uzman grubundan görüş alınmıştır. Uzmanlardan üç kriterin önem ağırlıklarını dilsel ifadelerle değerlendirmeleri ve 17 becerinin her bir kriter açısından belirleyicilik düzeyini aynı yöntemle puanlamaları istenmiştir. Elde edilen dilsel ifade değerlendirmeleri üçgen bulanık sayılara dönüştürülmüş ve uzman görüşleri eşit ağırlıklı olarak birleştirilmiştir. Kriter ağırlıklarının normalize edilmesinin ardından ağırlıklı normalleştirilmiş bulanık karar matrisi oluşturulmuş; bulanık pozitif ideal çözüm ve bulanık negatif ideal çözüme olan uzaklıklar Öklid mesafesi yöntemiyle hesaplanmış ve yakınlık katsayısı (CC) değerleri aracılığıyla beceriler sıralanmıştır. Analiz bulguları, çatışma önleme (CC=0,6714), manevra (CC=0,6348) ve kısıtlı durumlarda seyir (CC=0,6272) becerilerinin en yüksek önceliğe sahip olduğunu ortaya koymuştur. Takım çalışması, durumsal farkındalık, karar verme ve iletişim ve etkileme becerileri ise simülatör ortamında etkin biçimde ölçülebilir nitelikte olan temel davranışsal beceriler olarak öne çıkmıştır. Buna karşın meteoroloji ve oşinografi ile stres ve yorgunluk yönetimi becerilerinin köprüüstü simülatörü ortamında güvenilir biçimde ölçülmesinin sınırlı kaldığı anlaşılmıştır. CC değerlerindeki doğal kırılma noktaları esas alınarak beceriler üç katmana ayrılmış ve standart bir değerlendirme formu önerilmiştir. Katman 1 (CC ≥ 0,55) her simülatör uygulamasında standart olarak ölçülmesi gereken 10 beceriyi, Katman 2 (0,46 ≤ CC < 0,55) senaryo içeriğine bağlı olarak gözlemlenebilen 3 beceriyi ve Katman 3 (CC < 0,46) ilave ekipman gerektiren 4 beceriyi kapsamaktadır. Geliştirilen model, köprüüstü simülatör değerlendirmelerinde kurumlar ve değerlendiriciler arası tutarlılığı artırmaya yönelik uygulanabilir bir çerçeve sunmaktadır.
Özet (Çeviri)
Bridge simulators are recognized as one of the fundamental tools in maritime education, enabling seafarers to acquire and develop technical and behavioral skills in an environment that closely replicates real world conditions. Within the framework established by the International Convention on Standards of Training, Certification and Watchkeeping for Seafarers (STCW) and in line with the expectations of the maritime industry, simulator-based assessment has long been grounded in a competency-based approach. In principle, this means that assessment criteria should be clearly defined, measurable, and applied consistently regardless of who is conducting the evaluation. In practice, however, this is not always reflected in operational settings. Inconsistencies arising from assessors' subjective evaluations have been a persistent concern in both the academic literature and professional practice. Assessors naturally draw on their own professional experience and personal benchmarks, and this can lead to the same performance being scored quite differently by different assessors. The problem is especially pronounced in the assessment of behavioral skills, where the behavioral indicators being observed are inherently less clear-cut than the procedural standards used for technical skill assessment. This study was motivated by that gap between principle and practice. Its aim is to propose a model that makes bridge simulator evaluation more objective, transparent, and applicable by systematically determining how much each technical and behavioral skill should figure in the evaluation process. To build that foundation, seventeen skills were identified through a review of the relevant regulatory and industry literature: eight technical skills (T1-T8) and nine behavioral skills (D1-D9). The sources drawn upon include STCW, IMO Model Course 7.01 for management-level deck officers, IMO Model Course 7.03 for operational-level deck officers, the OCIMF and INTERTANKO Behavioral Competency Assessment and Verification Guide, and the IAMU Simulator Training Working Group report published in 2025. The technical skills are navigation in restricted waters, collision avoidance, maneuvering, emergency response, effective use of bridge communication equipment, effective bridge watchkeeping, voyage planning, and meteorology and oceanography. The behavioral skills are teamwork, communication, situational awareness, decision making, problem solving, leadership and management, critical thinking, conflict management, and stress and fatigue management. These seventeen skills were treated as alternatives within a Fuzzy TOPSIS framework and evaluated against three criteria: the effect of scenario design on assessment criteria (K1), the developability of skills through simulator training (K2), and the effect of briefing on assessment criteria (K3). Each criterion warrants brief elaboration. The first reflects a straightforward practical reality: not every skill can be assessed through the same scenario, and a scenario must be deliberately designed to elicit the behaviors it is meant to measure. The second recognizes one of the core advantages of simulator training that scenario can be repeated and debriefing sessions used as structured tools for skill development. The third acknowledges that the information provided to participants before an exercise, and in particular the behavioral expectations communicated during briefing, can meaningfully influence how certain skills are demonstrated during the session. Data were collected by consulting ten specialists who hold IMO Model Course 6.10 qualifications and are actively working as assessors in bridge simulator applications. In the first part, experts were asked to rate the importance of the three criteria using a seven-point linguistic scale. In the second part, they rated the significance of each of the seventeen skills with respect to each criterion using a second linguistic scale of the same structure. Because all ten experts shared the same professional qualification and were actively engaged in simulator assessment, no differential weighting was applied across the group. The linguistic responses were converted into triangular fuzzy numbers using the conversion scales defined by Chen (2000), and individual assessments were aggregated by computing arithmetic means. The Fuzzy TOPSIS procedure then followed its standard steps: a normalized fuzzy decision matrix was derived through linear scale transformation, since all three criteria were of the benefit type; the weighted normalized matrix was obtained by multiplying this by the fuzzy criterion weights; the fuzzy positive ideal solution was set at (1,1,1) and the fuzzy negative ideal solution at (0,0,0); and the distances of each skill from these ideal points were calculated using the Euclidean distance. Closeness coefficient (CC) values were then used to rank all seventeen skills. The results showed closeness coefficients ranging from 0.3789 to 0.6714, a spread that reflects meaningful differentiation among the skills in terms of their suitability for bridge simulator evaluations. At the top of the ranking, collision avoidance came first with a CC of 0.6714, followed by maneuvering (CC = 0.6348) and navigation in restricted waters (CC = 0.6272). These three technical skills rated consistently high across all three criteria, which is consistent with their established centrality in bridge simulator exercises and in competency-based assessment more broadly. They are sensitive to how a scenario is constructed, they respond well to the kind of iterative practice that simulators make possible, and the behaviors associated with them are sufficiently well-defined that briefing can meaningfully shape how they are demonstrated. Among the behavioral skills, teamwork ranked highest at fourth overall (CC = 0.6035), followed by situational awareness (CC = 0.5997), decision making (CC = 0.5857), and communication (CC = 0.5757). The fact that these four skills ranked immediately behind the top three technical skills is noteworthy, as it indicates that they are sufficiently observable and measurable in the bridge simulator environment to be assessed with reasonable confidence, a finding that aligns with the growing emphasis on behavioral skills in maritime safety literature. Emergency response (CC = 0.5595), problem solving (CC = 0.5562), and leadership and management (CC = 0.5504) ranked eighth through tenth respectively, completing Layer 1. Although their closeness coefficients are somewhat lower than those of the top-ranked skills, they can be reliably assessed through standard simulator exercises when scenarios are appropriately designed. Effective bridge watchkeeping (CC = 0.5296) ranked eleventh and marks the beginning of Layer 2, together with effective use of bridge communication equipment (CC = 0.4971) and voyage planning (CC = 0.4866). These three skills are observable within the simulator environment but their assessment depends to a greater degree on scenario content; they are therefore recommended for supplementary observation rather than standard scoring. Layer 3 contains the four lowest-ranked skills: critical thinking (CC = 0.4567), conflict management (CC = 0.4547), meteorology and oceanography (CC = 0.4146), and stress and fatigue management (CC = 0.3789). These skills present particular challenges for conventional simulator assessment. Meteorology and oceanography, while relevant to navigational decision-making, is difficult to develop and evaluate within the dynamic constraints of a simulator exercise. Stress and fatigue management presents an even more fundamental measurement challenge, as its reliable assessment typically requires physiological monitoring equipment such as heart rate sensors or EEG devices. Despite their growing presence in the literature, remain outside the scope of routine simulator practice. The criterion weights assigned by the expert group reinforced this overall picture. Scenario design effect received the highest consolidated fuzzy weight of (0.76, 0.92, 0.99), reflecting a shared professional conviction that the content of a scenario is the single most influential factor in determining what can actually be assessed. Developability through simulator training came second (0.58, 0.77, 0.92), and the effect of briefing third (0.40, 0.59, 0.75). Considered collectively, these weights explain why skills that depend heavily on specific scenario conditions, or that do not respond well to the kind of development the simulator environment supports, tended to rank lower in the overall analysis. Examining the distribution of closeness coefficients, consecutive CC values differed by between 0.003 and 0.016 across most of the ranking. Two transitions were considerably larger: a gap of 0.0208 between the tenth and eleventh-ranked skills, and a gap of 0.0299 between the thirteenth and fourteenth. These natural breaks were used to define the three-layer structure described above. Layer 1 (CC ≥ 0.55) contains the ten highest-ranked skills, which should be assessed as a standard component of every bridge simulator exercise. Layer 2 (0.46 ≤ CC < 0.55) contains three skills that are observable depending on scenario content and should be recorded as supplementary findings when they arise. Layer 3 (CC < 0.46) contains four skills whose reliable assessment requires additional methodological arrangements beyond what standard simulator practice provides. This three-layer structure formed the basis for a standardized assessment form. The form has three sections. In the first, each of the ten Layer 1 skills is scored on a ten-point scale, and the overall performance score is calculated as their arithmetic mean. In the second, Layer 2 skills observed during the exercise are recorded and rated by the assessor, though these ratings are kept separate from the final score to preserve comparability across sessions with different scenario content. In the third section, the assessor notes which Layer 3 skills would benefit from supplementary assessment and indicates the recommended method for each. To support the practical implementation of the model, several operational recommendations were also formulated. Recording simulator sessions on video is advised, both to promote consistent application of the form and to provide an objective basis for discussion in cases of disagreement. Where circumstances allow, having at least three independent assessors evaluate the exercise and compare their results would strengthen inter-rater reliability considerably. Assessors are recommended to have a minimum of ten years of sea service, and the involvement of company representatives in the process is encouraged as an additional measure to enhance transparency. Considered as a whole, the proposed model addresses two interconnected problems in bridge simulator assessment. By using the Fuzzy TOPSIS analysis to determine which skills are most suitable to simulator-based evaluation, it reduces the variability in assessment scope that currently exists across institutions and individual assessors. By translating those findings into a standardized form with clearly defined layers, it establishes the conditions for a more repeatable and comparable assessment process. In doing so, the study contributes to the ongoing effort to bring greater consistency and rigor to maritime education and training - an effort that STCW, IMO, and IAMU have each identified as a priority for the sector.
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