Replication data for: Integrating Adaptive Programming of Asynchronous Simulator Training for Motivated Goal Achievement in Professional Education

Publication Abstract:The application of cloud-based simulators has increasing momentum in maritime education and training as a virtual platform for supplementing professional training with task-specific simulation-based learning. Congruent with traditional simulator technology and training methods, this new condition allows for asynchronous and unlimited simulator access where participation in training sessions is at the discretion of the trainee. Furthermore, this provides a learning environment that can have adaptive features to the trainee characteristics with selectable complexity levels, automated feedback, and automated performance assessment. With the advent of this emerging training technology, the organization of how training is deployed, the new roles and expectations for trainees and instructors, and the application of new data-driven analytics are not yet well understood. This paper employs a quasi-experimental study to investigate trainee motivation, personality traits, and task performance using a novel training design. The study was administered remotely to a sample (N = 18) of first-year maritime students who first completed a knowledge acquisition phase before conducting a skill acquisition phase with repeated simulator training of a procedural task, and finally a performance assessment of the simulator scenario. Data was collected from (1) a multiple-choice knowledge test, (2) a short-scaled Big Five Inventory, (3) the Motivated Strategies for Learning Questionnaire, and (4) programmed simulator metrics. Results indicate that Extraversion correlates with motivation and self-efficacy predicts training performance. No significant relationship between prior knowledge and the training performance was found. The results can provide knowledge for implementation and delivery of remote simulator training in maritime education and training, as well as other fields.

论文摘要：基于云的模拟器（cloud-based simulators）在海事教育与培训中的应用势头日益强劲，其作为虚拟平台，可通过针对特定任务的模拟式学习补充专业培训。相较于传统模拟器技术与培训模式，这一新模式可实现异步且无限制的模拟器访问权限，参训学员可自主决定是否参与培训课程。此外，该模式可构建具备自适应功能的学习环境，可根据受训学员特质进行调整，同时支持自定义复杂度层级、自动反馈与自动化绩效评估。随着这一新兴培训技术的问世，培训部署的组织模式、受训学员与教员的新角色及职业期望，以及新型数据驱动分析方法的应用场景，目前尚未得到充分阐释与研究。本文采用准实验研究方法，结合全新的培训设计，探究受训学员的学习动机、人格特质与任务绩效表现。本研究以远程方式开展，受试样本为18名（N=18）一年级海事专业学生。受试者需依次完成三个阶段：首先是知识习得阶段，随后通过重复开展某一程序性任务的模拟器训练进入技能习得阶段，最终完成该模拟器场景的绩效评估。研究数据采集自四类工具：(1) 单项选择题知识测试；(2) 简版大五人格量表（Big Five Inventory）；(3) 学习动机策略问卷（Motivated Strategies for Learning Questionnaire）；(4) 预设模拟器运行指标。研究结果显示，外向性（Extraversion）与学习动机呈显著正相关，且自我效能感可有效预测培训绩效；未发现先验知识与培训绩效之间存在显著关联。本研究结果可为海事教育与培训及其他领域的远程模拟器培训的实施与落地提供理论参考与实践依据。