Developing a Blended Learning Model Through Collaborative and Case-Based Learning to Enhance Academic Achievement and Professional Skills of Nursing Students in the Tak Special Economic Zone

Abstract

This study aimed to develop and evaluate a blended learning model integrating collaborative and case-based learning to enhance academic achievement and professional skills among nursing students in the Tak Special Economic Zone. Employing a research and development (R&D) design, the study proceeded through four phases: (1) developing the instructional model, (2) constructing and validating research instruments, (3) implementing the model with nursing students, and (4) evaluating and refining the model. The instructional design, based on a 70% online and 30% face-to-face structure, incorporated seven collaborative case-based steps (SDSSESP) to foster problem-solving, teamwork, and professional attitudes. A purposive sample of 35 second-year nursing students enrolled in Adult Nursing I participated in a one-group pretest-posttest experiment. Data were collected using achievement tests, problem-solving measures, teamwork skill assessments, professional attitude scales, and satisfaction questionnaires. Results demonstrated significant improvements in students’ academic achievement, problem-solving abilities, teamwork skills, and professional attitudes after participation (p < .01). Expert validation confirmed the model’s appropriateness at a high level, while students expressed strong satisfaction with its implementation. The findings indicate that blended learning, when systematically integrated with collaborative and case-based approaches, effectively enhances both cognitive and professional competencies essential for 21st-century nursing. This model is particularly suitable for resource-constrained and diverse learning contexts, such as border and special economic zones. Practical implications suggest broader adoption of blended, collaborative, and case-based strategies across nursing curricula, while future research should employ comparative, longitudinal, and technology-enhanced designs to further refine and validate the model.