THE IMPACT OF THE COMPUTER-ASSISTED FLIPPED LEARNING MODEL ON TEACHER CANDIDATES’ RESEARCH SELF-EFFICACY

This study examines the impact of the Computer-Assisted Flipped Learning Model (CAFLM) on the research self-efficacy (RSE) of pre-service teacher candidates, particularly in pre-school and special education departments. Utilizing a two-group pretest-posttest experimental design, 61 participants (31 pre-school and 30 special education teacher candidates) were assessed over a 16-week scientific research methods course. The Scientific Research Self-Efficacy Scale (SRSES), consisting of six components and 37 items, was used as the data collection instrument. The key findings reveal a significant improvement in participants' RSE, with no considerable differences observed between the two departments. In this study, the CAFLM, which involves engaging with instructional content (e.g., educational videos, digital materials, and online resources) before class and applying that knowledge through interactive classroom activities played a central role. The use of digital tools not only enabled flexible and self-paced learning but also supported independent problem-solving and collaborative learning processes, both of which are crucial for fostering mastery experiences that enhance self-efficacy. Participants engaged in watching preparatory videos, participating in in-class discussions, and writing research reports, all supported through computer-assisted platforms. The results showed considerable improvement in overall RSE and in most of the sub-dimensions. Although no statistically significant differences were found in the post-test results of the "definition of the problem" (DP) and "identification of the hypothesis" (IH) subscales, increases in scores were observed. Ultimately, both groups demonstrated improved research self-efficacy following various computer-supported research tasks. The findings suggest that while the field of study does not significantly influence the effectiveness of FLM, the integration of computer assistance within the FLM framework can significantly enhance research skills and self-efficacy among teacher candidates.