A Pilot Study of the Effects of Instructional Design with Learning Analytics on a Computer Simulation-Based Learning Environment

Author(s):  
Yuling Hsu ◽  
Sheng-Kuei Hsu
Author(s):  
Ujin Lee ◽  
Heeseung Choi ◽  
Yeseul Jeon

Simulation-based communication education has improved nursing students’ communication knowledge and skills. However, communication patterns that students commonly exhibit in simulated situations and students’ responses to specific clinical situations have not been systematically examined. The specific aims of the present study were (1) to identify non-therapeutic communication patterns that nursing students exhibit in simulated situations in the computer simulation-based education (ComEd) program, and (2) explore students’ responses to challenging clinical situations. This study used a mixed-method research design and a convenience sampling method to recruit participants. Frequency analysis and a conventional content analysis method were used to analyze answers provided by participants. A total of 66 students from four Korean nursing schools participated in the study. “False reassurance” was found to be the most common non-therapeutic communication pattern used by nursing students. Nursing students had difficulty in clinical situations such as reporting a patient’s condition to a doctor, communicating with a patient and perform basic nursing skills at the same time, and managing conflicts between patients. Technology-based communication simulation programs, which reflect various clinical situations, are considered a new alternative that can supplement the limitations of clinical practicum and improve the quality of nursing education.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yashuang Wang ◽  
Yan Ji

Abstract Background Student engagement can predict successful learning outcomes and academic development. The expansion of simulation-based medical and healthcare education creates challenges for educators, as they must help students engage in a simulation-based learning environment. This research provides a reference for facilitators of simulation teaching and student learning in medical and health-related majors by providing a deep understanding of student engagement in a simulation-based learning environment. Methods We conducted semi-structured interviews with ten medical and healthcare students to explore their learning types and characteristics in a simulation-based learning environment. Thematic analysis was used to analyse the data. Results The interviews were thematically analysed to identify three types of student engagement in the simulation-based learning environment: reflective engagement, performance engagement, and interactive engagement. The analysis also identified eight sub-themes: active, persistent, and focused thinking engagement; self-directed-learning thinking engagement with the purpose of problem solving; active “voice” in class; strong emotional experience and disclosure; demonstration of professional leadership; interaction with realistic learning situations; support from teammates; and collegial facilitator-student interaction. Conclusions The student interview and thematic analysis methods can be used to study the richness of student engagement in simulation-based learning environments. This study finds that student engagement in a simulation-based learning environment is different from that in a traditional environment, as it places greater emphasis on performance engagement, which combines both thinking and physical engagement, as well as on interactive engagement as generated through interpersonal interactions. Therefore, we suggest expanding the learning space centring around “inquiry”, as it can help strengthen reflective communication and dialogue. It also facilitates imagination, stimulates empathy, and builds an interprofessional learning community. In this way, medical and healthcare students can learn through the two-way transmission of information and cultivate and reshape interpersonal relationships to improve engagement in a simulation-based learning environment.


2018 ◽  
Vol 7 (3) ◽  
pp. 1124 ◽  
Author(s):  
Andino Maseleno ◽  
Noraisikin Sabani ◽  
Miftachul Huda ◽  
Roslee Ahmad ◽  
Kamarul Azmi Jasmi ◽  
...  

This paper presents learning analytics as a mean to improve students’ learning. Most learning analytics tools are developed by in-house individual educational institutions to meet the specific needs of their students. Learning analytics is defined as a way to measure, collect, analyse and report data about learners and their context, for the purpose of understanding and optimizing learning. The paper concludes by highlighting framework of learning analytics in order to improve personalised learning. In addition, it is an endeavour to define the characterising features that represents the relationship between learning analytics and personalised learning environment. The paper proposes that learning analytics is dependent on personalised approach for both educators and students. From a learning perspective, students can be supported with specific learning process and reflection visualisation that compares their respective performances to the overall performance of a course. Furthermore, the learners may be provided with personalised recommendations for suitable learning resources, learning paths, or peer students through recommending system. The paper’s contribution to knowledge is in considering personalised learning within the context framework of learning analytics. 


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