The study of optimal best practice within the context of academia has produced both empirical and theoretical contributions. Optimal best practice, also coined as optimal functioning, is concerned with a person's personal best-that is, what is the best that I can do for this academic subject? Research in the social sciences has, to date, explored different types of optimal best-physical, cognitive, emotional, and social. What is of considerable interest, as a related matter, is a question of how a person reaches and experiences a level of optimal best practice. Recent research development, for example, has explored various conceptualizations of optimal best practice-for example, one distinctive theoretical model, the Framework of Achievement Bests [1, 2], makes a concerted effort to explore the underlying process of optimization-that is, in this case, how an optimal level of best practice is achieved. The present study, as detailed below, investigates via means of non-experimental data a theoretical model pertaining to the achievement of optimal best practice. This examination, we postulate, would enable us to add clarity and provide additional theoretical insights the operational nature of the process of optimization. The operational nature of optimization, as described in our recent research [1, 3], emphasizes three major tenets: (i) the main sources of a person's optimal best practice, (ii) the potential 'optimizing' influences of three comparable agencies on the achievement of optimal best practice (i.e., personal resolve, social relationship, and personal self-efficacy), and (iii) the impact of optimal best practice on future adaptive outcomes (i.e., academic striving and personal well-being). We explored this topic via means of the use of a non-experimental, correlational design with participants drawn from Taiwanese university students (N = 1010). Structural equation modelling (SEM) produced evidence, which empirically supported existing research [1, 3] and substantiated our knowledge of the concept of optimal best practice. Evidence established from the present study has also assisted us to identify one pervasive issue, which we call for further research development-namely, to consider, design, and develop an appropriate methodological approach that would enable researchers to accurately measure and assess the process of optimization. Finally, in terms of teaching and learning, we acknowledge that our research investigation has provided some insights into potential educational practices for implementation.
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